How Sanity.io manifests the value of headless CMS

In our recent white paper, we stated that customer experience will overtake price and product as the key brand differentiator in 2020. We also discussed how the rapid evolution of both customer expectations and CX technologies is a wakeup call for both CX and IT leaders.

So, that’s it! Any business failing to deliver omnichannel customer experiences or remaining inactive across their website, mobile application, voice assistant, email, social media profiles, or online customer support is sure to face peril. This has set in a new level of expectation as to how digital content should be managed. Definitely, this puts the onus on companies to adopt a headless content management system (CMS). 

Now, the question is what’s wrong with the traditional CMS? If WordPress, Drupal, or Joomla allows you to have both the CMS and the website’s design in one place, wouldn’t it be easier to make updates and manage your content seamlessly? Then why did leading brands like Cornerstone, Cloudflare, and Eurostar move to Sanity, one of the top headless CMS platforms? 

Here, we tell you what’s a headless CMS and why many industry leaders have adopted Sanity.io. 

The Headless CMS Movement 

Remember the “pre-CMS era” where you had to update HTML pages manually and upload them on the website via FTP and perform a lot more steps? The birth of popular content management systems like Drupal and Joomla not only gave us relief, also did they tempt us with convenience. However, these legacy platforms often force us to solicit assistance from developers working on a specific CMS and require us to spend more time, resources, and budget for maintenance and enhancements. 

A traditional CMS ideally fits an enterprise-level small business website or a personal website, especially if you do not have to share content with multiple digital devices or platforms. With cross-channel content dissemination at the speed of light becoming the Holy Grail, the monolith, single storage feature offered by traditional CMS is easily giving way to headless CMS.   

Read more: Top 6 Tech Stacks That Reign Software Development in 2020

Decoding Headless CMS 

In simple terms, a headless CMS is a content-first CMS where the content repository (body) is decoupled/separated from the presentation layer (head). It’s a back-end only content management system that makes content accessible to external clients for display through APIs. 

The result: Even a non-developer can create or edit content without getting worried about how the content will be displayed or consumed by the external systems. If you need to publish content on multiple platforms all at once, headless CMS is the best choice. 

The beauty: Headless CMS is front-end agnostic. You can choose the framework or tool you like for displaying content to the end-user. It allows front-end developers to solely focus on the presentation layer without thinking about how the content will be managed. 

5 reasons to go for Sanity, the popular headless CMS

“Build with structured content” is the byword of Sanity. However, the platform makes no assumptions about how your content is structured, created, validated, and presented. This offers you the flexibility to deliver structured content into any digital devices or applications via Sanity’s real-time, cloud-hosted APIs and customizable open-source editing environment.

1. Get started in no time

You can quickly get started with Sanity.io by downloading CLI from npm and use it to launch a new project. Alternatively, you can go to Sanity’s starter projects that will help you get started in minutes with its preconfigured Sanity Studio and a functional front-end with a range of frameworks to choose from, all deployed to Netlify with source code on GitHub.

2. Superior editing features

Sanity’s editor or the Sanity Studio is a flexible, open-source application that allows you to define content models with simple JavaScript. A single-page app built with React.js, Sanity Studio allows you to customize or extend it using your own React.js components. Its advanced features help you modify workflows for your editors. Along with customization, Sanity Studio offers core features like Block Content, Structure Builder, and a Dashboard plugin.

3. Exceptional APIs

The primary reason for choosing a headless CMS is its API-first pattern that allows you to access the content through APIs.

Sanity offers two powerful APIs for reading, writing, querying, and patching documents:

• api.sanity.io which is the live uncached API
• apicdn.sanity.io which is the CDN-distributed, cached API

Sanity also supports deploying GROQ and GraphQL APIs to query your content. The platform’s Data Store resides in the cloud and can be accessed via Sanity API either using Sanity’s client libraries or through the HTTP API directly.

4. Matured technology stack

Sanity is a cloud-hosted CMS with a real-time content studio and hence all the data is synced instantly. The underneath architecture involves mature technologies such as  PostgreSQL, ElasticSearch, and JavaScript, and the blazing-fast React. It doesn’t save HTML, XML, or rich text in the database, but in rational object structures. For instance, if you want Alexa to read from your text fields, then you don’t have to parse HTML. Sanity comes packed with its well-maintained JavaScript, HTML, and PHP clients allowing you to be up and running fast with the front-end framework of your choice.

5. User-friendly headless content models

Though you require someone with basic JavaScript knowledge to get started with Sanity, it isn’t hard to find a person who is familiar with the popular web programming language. Sanity enables content editors, visual and interaction designers, and technology professionals to collaborate on building the information architecture. Front-end developers can save their efforts by accessing content fields instantly through APIs.  

Need more reasons to fall for headless CMS? 

To give you an example, Sanity prevents you from getting “locked-in”. Despite being a SaaS platform, Sanity allows you to easily export your content and use it wherever you need. Same with the front-end frameworks that we saw above. Customized editorial experiences, structured content approach, minimal hidden costs, pay-as-you-go pricing model, and a number of stunning features will make you say “Yes” to the headless CMS model.

If you would like to know more about Sanity.io or any other headless CMS platform that you’re currently considering, drop us a line immediately.

How Can Your Business Benefit from Fog Computing?

How much data do we create every day? The World Economic Forum reports that the entire digital world is expected to reach 44 zettabytes by 2020. So, each day, we witness the colossal growth of data and this pace is only increasing with the growth of IoT. The agility and flexibility of big data applications are the foundation of the Internet of Things (IoT). The escalation of IoT has resulted in an increased volume of digitally generated data and managing that data has become a major challenge. This has led to the emergence of fog computing – an answer to the new challenges of computing technologies. 

Read more: Gearing up for IoT in 2020

Defogging The Term Fog Computing

Let us start by defining it. 

What is fog computing?

Fog computing is a decentralized computing infrastructure in which computing resources such as data, computers, storage, and applications are located between the data source and the cloud. This term refers to a new breed of applications and services related to data management and analysis. 

According to Mung Chiang, Dean of the Purdue University, “fog provides the missing link for what data needs to be pushed to the cloud, and what can be analyzed locally, at the edge.” In simple terms, fog computing is a distributed network fabric that stretches from the outer edges of data creation to the point of storage.

Are fog computing and edge computing the same?

Edge computing is a subset or a component of fog computing. For example, if fog computing is compared to a basket of various fruits, edge computing would be one fruit from a single variety. 

Edge computing refers to data being analyzed locally, at the point of creation. Fog computing encapsulates edge processing as well as the network connections required to bring that data from the edge (point of creation) to its endpoint. 

Evidently, fog computing and edge computing are complementary. 

Difference between fog computing and cloud computing

Just as the literal fog is a cloud closer to the ground, fog computing is stationed as a layer to reduce the latency in hybrid cloud scenarios. Cloud computing forms a comprehensive platform that helps businesses with the power to process important data and generate insights. Fog computing is like the express highway that supplies computing power to IoT devices which are not capable of doing it on their own. 

Read more: Hybrid Cloud Infrastructure: How It Benefits Your Business

How Does Fog Computing Work?

Fog computing uses the concept of ‘fog nodes.’ These fog nodes are located closer to the data source and have higher processing and storage capabilities. Fog nodes can process the data far quicker than sending the request to the cloud for centralized processing.

The cloud is getting cluttered due to the enormous number of devices connecting to the internet. Since cloud computing is not viable in some cases, it has become necessary to use fog computing for IoT devices. It can handle the enormous data generated by these devices. 

When implemented, fog-empowered devices locally analyze time-critical data that includes alarm status, device status, fault warnings, and so on. This minimizes latency and prevents major damage. Fog computing can effectively reduce the amount of bandwidth required, which in turn speeds up the communication with the cloud and various sensors. 

Fog computing example: 

If a user with a hand-held device wants to review the latest CCTV footage from a locally positioned IoT security camera, he would need to request the stream from the cloud since the camera does not have storage. This could take a bit of time, which can be eliminated with fog computing, where a local fog node can be accessed for video streaming which is far quicker. 

Step-by-step Fog Computing Process:

• Signals are wired from IoT devices to an automation controller which executes a control system program to automate those devices. 

• A control system program wires data through a protocol gateway.

• Data is converted into a protocol such as HTTP so that it can be understood easily by internet-based services. 

• A fog node collects the data for further analysis. 

• It filters the data and saves it for later use. 

Read More: Fog Computing: The Catalyst For Efficient Data Processing

Key Takeaways for Your Business

• Increased business agility: It is evident that fog computing is cost-effective because it makes the production of revenue-generating products and services more efficient. It accelerates rollout cycles, broadens revenue bases, and reduces costs.

This revenue stream creates value for IoT fostering highly functioning internal business services. Fog computing also provides a common framework for seamless collaboration and communication helping OT and IT teams to work together to bring cloud capabilities closer.  

• Privacy control: Fog computing facilitates better control of privacy because you can process and analyze sensitive data locally instead of sending it to a centralized cloud for analysis. It also enables the IT team to track, monitor, and control any device that collects or stores data.
• Data security:  Since fog computing allows you to connect multiple devices to a network, it helps identify threats such as potential hacks, or malware. Additionally, such identified threats can be curbed at the device level without risking the entire network. 

The Future is Fog Computing

Fog computing has several advantages over cloud computing. Fog computing can boost usability and accessibility in various computing environments. Soon, cloud computing for IoT may fade away but fog computing will take over. IoT is seeing an impressive growth rate and so it needs a special infrastructure base that can handle all its requirements. Fog computing is the key to accomplish this critical work. So get in touch with us and let’s get this happening for your business.

Data Lake vs Data Warehouse

A data lake is a location where new data can enter without any hurdles. Since any kind of data can reside in a data lake, it is a great source to unearth new ideas and experiment with data. However, due to this openness, it suffers from a lack of meaningful structure. The larger business audience may find that the data lake is a mess. This is where the scalability traits of the data warehouse gain significance. In data warehousing, we try to match dimensions and measures into queryable components that are consistent. This makes it easier for an ever-scalable audience to consume this data. 

Let us now take a deep dive and compare the properties of a data lake and a data warehouse.

Read more: How Data Warehousing Adds Value To Data Visualization & Reporting

7 key differences between data lake and data warehouse

1. Type of Operation:

• A data warehouse is used for Online Analytical Processing (OLAP). This includes running reports, aggregating queries, performing analysis, and creating models such as the OLAP model based on whatever you want to do. These operations are carried out typically after your transactions are done. For example, you want to check all the transactions done by a particular client. Since the data is stored in a denormalized format, you can easily fetch the data from a single table and showcase the required report.
• A data lake is used typically to perform raw data analysis. All the raw data i.e XML files, images, pdf, etc. are just gathered for further analysis. While capturing data, you don’t have to define the schema. You may not know how this data can be used in the future. You are free to perform different types of analytics to uncover valuable insights.

2. Cost of storing data:

• In data warehouses, the cost of data storage is high. This is because the software used by these data warehouses are expensive. Additionally, the cost of maintenance is also high since it consists of power, cooling, space, and telecommunications. Another point to consider is that since a data warehouse contains large amounts of data in a denormalized format, it tends to take up a lot of disk space.
• Contrarily, in data lakes the cost of data storage is low. They use open-source software which costs less. Also since the data is unstructured, data lakes can scale to high volumes of data at low cost. 

3. Schema:

• Data warehouses use schema-on-write. Before storing the data, it has to be transformed and provided for application in analytics and reporting. You need to know for what purpose you’ll be using the data prior to importing it into the data warehouse. As new requirements arise, you may have to reevaluate the models that were defined earlier.
• On the other hand, data lakes employ schema-on-read. Without the necessity of a single schema, users can store any kind of data in the data lake. They can discover the schema later while reading the data. This means different teams can store their data in the same place without relying on the IT departments to write ETL jobs and query the data.

4. Data Quality:

• A data warehouse contains high-quality data. As the data undergoes extreme curation before storage, it can be considered as the central version of the truth. 
• A data lake contains raw data that may or may not be curated.

Read more: Data Visualization vs. Data Analytics – What’s the Difference?

5. Users:

• Typically business professionals who deal with reporting use data warehouses. Again, since the operation costs of a data warehouse tend to be higher, large and established organizations that deal with tons of data opt for it. 
• Data scientists and analysts generally use data lakes. With raw data the possibilities are endless. They can perform various types of analytics to glean insights and identify patterns to convert the data at hand into valuable information. 

6. Security:

• Data warehouses tend to store extremely sensitive data for reporting purposes. These could be compensation data, credit card information, healthcare data, and so on. The data security for data warehouses is mature and robust since this technology has been around for quite a while now. Only authorized personnel can access the data warehouse.  
• Data Lake is a relatively new technology and hence data security is still evolving. As mentioned, a data lake is created using open source technologies. Therefore its data security is not as great as that of a data warehouse.

7. Technology:

• Data warehouse applications use relational database technologies. This is because relational database technologies support quick queries against structured data.
• The Hadoop ecosystem is well-aligned to the data lake approach because of its agility. It can easily scale to large volumes and can handle any structure of data. 

Read more: Power BI or Tableau: Which is the better choice for your business

How both data lake and data warehouse can go hand in hand

Both data lake and data warehouse are the principal constituents of modern data architecture. A data lake usually serves as the starting point from where organization-wide data is onboarded. It is also the stage at which the data warehouse structures its data. An organization that incorporates both data lake and data warehouse will exhibit the traits of entrepreneurship and diligence, which means the organization will be both open-minded and scalable. 

The BI industry has tools that cater to highly unstructured data lakes that enable open-minded discovery. Also, there are tools that are designed to scale as a structured information delivery platform concurrently with your data warehouse. Though these tools oppose one another, they have very little in common. They are purpose-built according to the needs of an organization. So before choosing a tool you need to determine which one would be right for your needs and help your organization grow. Contact us now for more information!    

Transforming Businesses with RPA- Leading Use Cases in HR and Banking

Various organizations use RPA tools to automate simple to complex tasks and perform them with minimal or no human intervention. 

From an IT perspective, you tend to bucket all RPA uses cases into data integration or testing. However, from a business perspective, you need to find out how to get a better time to value and how to overcome obstacles that hinder the business value. Then you can determine use cases that fit into this characterization. 

For example, you want to roll out a change in your business process, and need integration into another system. You can do that in two ways:

• either through APIs and get into the IT changed management routine, 
• or by using RPA to drive interfaces without an API and get the change rolled out in weeks instead of months. 

So, time to value is the calculation that businesses need to do, and check whether the change is worth it. 

Read more: What Makes a Business Process Apt for Automation

Suppose you have to perform tasks that are very repetitive in nature – like filling in excel forms, web forms, things like visual basic or word with data which you already have access to, or which you need to aggregate from various systems. Here you can have an RPA bot to pull that data or even push out that data to multiple systems. You won’t have to rekey that information manually. You can always use an RPA bot to do that in an automated fashion. In both these cases, you can write integrations or you can have a system do it for you. 

RPA gives you a way to configure that behavior rather than write a code for it. In other words, RPA use cases need to be data-intensive, rule-driven, and repetitive. The drivers almost always tend to be time to value, time to market, and so on.

Now that you’ve understood where to use RPA in your business, let’s have a look at some of the use cases. 

RPA Use Cases in HR 

According to UiPath, 40% of your HR professionals’ time can be reclaimed using RPA. Robotic Process Automation can be combined with your existing HR systems like SAP or Workday that allows you to create digital process automation with ease. Here are the two key HR areas where automation leads to transformation.

1. Payroll: 

Payroll operations consist of a large number of repetitive, rule-based tasks with activities like data collection, calculations, and scheduling tasks. Payroll workers have to collect data from various departments or units in different formats. The next step is data validation and entering that information into other applications. All these tasks are prone to error. 

These activities can be automated using RPA technology since all the data that payroll staff deals with is structured. RPA can make payroll more organized without using expensive software. 

The benefits of RPA in payroll are improved accuracy, lower costs due to reduced manual labor and data security. Since the number of menial, time-consuming tasks performed by employees is reduced, they can focus on tasks with higher strategic value.

2. Onboarding and offboarding:  

Every time you get a new employee, the candidate’s details have to be uploaded to all systems that you use. They may need a Windows account, access to your time reporting tool, email addresses, IT equipment, and so on. If someone from the HR team manually enters all this data they would be stuck in mundane tasks. Instead, you can have a script doing these repetitive tasks. With RPA, you can automate the entire onboarding procedure since the process is the same for every new employee. 

Employee exits too, have to be managed consistently. Manual processing makes these tasks error-prone and may raise auditory concerns. If RPA is implemented in this case, the bot analyzes the incident to find out which tasks need to be executed. It notifies the IT team to terminate access and recover the equipment, terminates the employee from the HCM, revokes system access, generates exit documents, and processes final payments. 

Read more: Jaw-dropping Facts about Robotic Process Automation

RPA Use Cases in Banking

A slow economy and rising customer expectations have caused banks to look for cost optimization methods. The back-end processing activities in the banking sector consist of tasks that are rule-driven, repetitive, labor-intensive, and high in volume. RPA technology can help to automate these processes, thus eliminating the need for human intervention. Here are the two major banking functions that can be automated for improved results.

1. Loan application processing: 

The processing of loan applications is a tedious process. For document verification, employees need to manually verify different documents and associated information and then organize all data into a single file. Very often, employees get stuck in this task and spend too much time on it. RPA employed in this procedure can automate the whole process by opening different web portals and validating the information. The bot then initiates an email to the employee for a final decision. Thus, the bot helps to save valuable time and improves the time to client response.

2. Account opening: 

The account opening process is cumbersome, time-consuming, and prone to errors. RPA can help speed up this process and make it more accurate. Bots draw out information from forms and enter it into separate host applications. Thus RPA eliminates errors and improves the quality of data in the system.

Read more: How Robotic Process Automation Simplifies Business Operations

RPA tools have the potential to help various industries improve efficiency, drive faster operations, and reduce costs than most automation techniques. RPA is gaining popularity as enterprises try to counter competition, increase productivity, and meet customer expectations. Early adopters of RPA have reaped its benefits and its high time that you did too. Get in touch with our experts to learn more about how RPA can simplify your business operations. 

6 Hot Technologies that Handhold Businesses Amid COVID-19 Impact

The COVID-19 pandemic has had wide-ranging ramifications for several businesses. Forrester predicts that the retail sector will endure a 2.1 trillion-dollar loss in 2020 due to COVID-19. It also said that it will take four years for retailers to experience the growth seen before the pandemic. As COVID-19 continues breathing threats down the neck of businessmen, hot technologies are emerging as a relief to counteract them and lead businesses towards their goals. We will discuss a few of these specific technologies such as cloud, eCommerce, eLearning, automation, virtual collaboration, and contactless services that can help you minimize the effects of COVID-19 on your business. 

Read More: Fingent’s Response to COVID-19 Business Implications

1. Cloud Adoption During COVID-19

With physical interaction no longer being an acceptable form of communication, organizations and institutions have had to swiftly shift to digital solutions to retain productivity. The domino effect of COVID-19 was seen in various sectors, accelerating the adoption of facilities for seamless remote work. Cloud computing has emerged as an essential technology for critical application and scalability of infrastructure in this regard. 

Companies from various sectors are now starting to realize the benefits and value of cloud computing as far-reaching beyond the scenario created by the pandemic. As a result, businesses will have to scale up their digital transformation efforts and invest in cloud resources without delay. If anyone had reservations about investing in cloud computing before this, COVID-19 has proved that its necessity is indisputable. 

Read More: 5 Trends That Will Transform Cloud Computing in 2020

2. E-Commerce

CCInsights reported that as of 21 April 2020, US and Canadian e-commerce orders have seen a 129% increase.

With restrictions on the number of people that can be gathered in one place, gone are the glory days of shopping malls and brick and mortar stores. COVID-19 has changed shopping behaviors overnight, necessitating brands to adapt and be flexible to meet changing needs. 

For example, the Buy Online Pick up In Store (BOPIS) capability has become vital to maintaining sales volume with the restrictions in mind. A good example of this is the mobile phone industry. When foot traffic is curbed, then Mobile Point of Sale programs can be set up to take orders and payment at the same time for business continuity. Membership or Loyalty cards can be now digitalized through mobile applications. 

Read More: How a Smart Product Ordering System Helps Retailers and Wholesalers

3. Virtual Collaboration

Many developed nations are now stipulating that employees of non-essential businesses work remotely for an indefinite time, making video conferencing vital.  Schools, colleges, and universities are also leveraging video conferencing platforms through live or recorded lectures. 

This has brought many virtual collaboration solutions to the forefront that facilitate video conferencing, instant messaging, task and calendar management, work collaboration, file sharing, attendance tracking, and so on. A few examples include Zoom, DingTalk, WeChat Work, Zoho Remotely, and so on. 

At Fingent, we use InfinCE, a powerful cloud-based enterprise collaboration software that offers support for remote work. 

Read Our Case Study: How Fingent enabled a smarter digital workplace solution for Sony Mobile

4. E-Learning 

During this time of crisis, the entire education ecosystem is coming together to ensure that students do not suffer. Educational applications, platforms, and resources offer functionalities across multiple categories such as:

• Resources to provide psycho-social support
• Digital learning management systems
• Digital systems designed for use on basic mobile phones
• Massive open online course platforms 
• Self-directed learning content
• Mobile reading applications
• Tools for teachers to create digital learning content

Read More: E-Learning Taking A New Front: How Can LMS Technology Help

5. Automation

Automation has been helping businesses mitigate disruption by enabling them to stay connected across teams and systems while maintaining customer support in times of uncertainties such as this pandemic. 

Robotic Process Automation improves the efficiency and reliability of work outcomes and automates the time-consuming, repetitive tasks that weigh down intelligent workers. The benefits are:

• Digital workers do not need to have the weekend off. They can work 24 hours a day, 24/7 to respond to spikes in business activity. 
• They do not have travel restrictions nor are they at the risk of COVID-19 infection or affected by physical office closure. 

During the pandemic, companies that have already invested in automation technologies are doing exponentially better than those who did not. It is obvious, that automation can pave the way for a better future.

Read More: How Automation Ensures Businesses Stay Afloat During COVID-19 Crisis

6. Contactless Services

The coronavirus pandemic has driven a preference for self-service purchasing, boosting contactless services. Consider a few examples available now and upcoming in the future: 

• Dining experience: Technology can take care of everything: reserving a table at the restaurant, pre-ordering your food, digital valet services, contactless seating, contactless payment, and online feedback.
• Contactless payment: It lets shoppers integrate their payment information to their loyalty account through an app and then use a QR code for payment through self-checkouts. 
• Contactless delivery: This ensures end-to-end hygiene because a customer places an order, makes the payment online, and gets the food delivered without ever coming in contact with the delivery agent. 

Read More: Contactless Services: The New Normal in Retail

Grab a Slice of Hot Technology

While the end of the pandemic remains elusive, capturing even a slice of these hot technologies could make a huge difference to businesses. They can even help smaller businesses gain a stronger foothold during this pandemic and into the future. Get in touch with us and help us guide you through this pandemic by implementing the right technology solutions for your business. 

The Need for Digitalization

Digital technologies have penetrated into every aspect of our lives, transforming the way we seek and receive information. For instance, today, we search for products and services on search engines rather than in yellow page directories and other offline media. We communicate our experiences with other people through chats, email, blogs, or social media posts. In other words, the media we use, the content we consume and share, the customers we engage with – all benefit from digitalization and digitized data.

Read More: A Road Map To Digital Transformation in 2020

Why is digitalization inevitable for businesses and how can organizations benefit from it?

Before we discuss the advantages of digitalization, we need to understand the difference between digitization and digitalization. According to Gartner’s IT Glossary, “digitalization is the use of digital technologies to change a business model and provide new revenue and value-producing opportunities, whereas “digitization is the process of changing from analog to digital form.”

Digitalization is already influencing the way we do business

Digitalization already has had an impact on our business – from the way we acquire and retain customers to the way we present our business and manage our reputation. While in the past, brick-and-mortar stores were sufficient to establish your business, now consumers want to know what services or products you offer before deciding to make the purchase. 

Today, businesses have to be in close proximity with their customers to find out about their opinions and improve customer experiences. When you know more about your customers, you have more data at hand. Digitalization helps apply this data to make better business decisions. 

With digital technologies, you have more tools that make work easier. This can lead to increased productivity and reduced costs. Digital tools such as dashboards and collaboration tools such as messengers and video chats help align your employees with business goals and improve internal communication. 

What does digitalization mean to you?

Digitalization does not just mean implementing various technologies into daily business. You need to also rethink your business and operating models to implement the technology. Technology is just the tip of the iceberg. Together with it, you need to understand your digital maturity as an organization. Technology does enable digital engagement, but you need to assess the big picture of what digitalization means to your business – whether you are a public organization, a small private company or a global player. To gain control over customer relationships, you need to develop end-to-end strategies to reach customers. 

Top 3 opportunities for digitalization

1. Converting excel sheets to dashboards

In any organization, we find an opportunity gap between the growth of the company on a revenue basis and the growth of the support staff. This part of the company needs to focus on improving automation and scalability to better support the rest of the company. 

Read More: How Automation Ensures Businesses Stay Afloat During COVID-19 Crisis

Most of us still enter information in excel spreadsheets. For example, if we track our projects (work in progress), contracts, savings, etc. in separate spreadsheets, we’re only entering the same data many times. Converting to dashboards can help you quickly view and analyze your entire data in one place. 

Along with consolidated views, dashboards provide opportunities for business intelligence by allowing users to display only what’s required through the use of filters. Once you start adding insights and recommended actions along with the summary, the dashboard becomes more useful by closing any communication gaps between various departments in your company. In short, you save time, provide clear communication, and drive business goals. 

2. Document Management systems

The advent of digitalization has opened up new avenues of data, making its’ management complex. The traditional file and paper methods have become archaic as well as cumbersome. Document management systems have proved themselves indispensable for businesses of all sizes. 

With digitalization dominating the trend in business, enterprises are looking for new ways to streamline documentation by using various automation techniques. The rise of cloud-based document management systems has simplified the creation and sharing of digital documents for enterprises. 

Read More: Top 6 Reasons Why You Should Move to a Cloud-Hosted ERP

Managing huge volumes of data has also become relatively easy. Today you have document management systems that vary in scope from simple systems that cater to small enterprises to more sophisticated ones that cater to large global enterprises. Document management systems reduce physical storage, enable quick access of documents, promote security, make maintenance and customization easy, and reduce monotonous tasks.

3. OCR Technology

Another technology that helps with the digitalization of businesses is OCR. The ability of Optical Character Recognition (OCR) software to automatically extract data from an image file or scanned document has helped businesses to streamline their operations. It reduces the time required in manual data entry and extraction. A robust and accurate OCR can extract data from multiple document formats. Thus, it saves time in data collection, reduces human effort, and aligns business processes with customer needs. AI-powered OCR eliminates manual entry, thereby reducing errors and improving productivity. Businesses that are equipped with AI-powered OCR technology can stay afloat in the digital wave that has swept across the world.

Digitalization can drive recovery from COVID-19

As the coronavirus pandemic continues to take a toll on people’s lives, it has also stimulated change in the social, personal, economic, and corporate forefronts. The focus has now shifted from growth, business development, and digitalization to just riding out the storm, that is, ensuring business continuity. However, organizations should not lose sight of the long-term effects of the crisis. Companies would have to rethink their business models according to changing customer demands. This crisis has forced organizations to invest in their digitalization strategies to establish sustainability. 

Read More: Business Process Re-engineering: Facing Crisis with Confidence

Companies need to direct their digitalization strategies towards increasing resilience and optimization. Rather than just focusing on increasing productivity, a sustainable and comprehensive digitalization strategy should focus on maintaining productivity during future challenges. Write to us to know more. 

What is Exploratory Data Analysis?

Exploratory Data Analysis (EDA) is a statistical approach used to analyze data and produce descriptive and graphical summaries. Analysts may or may not use a statistical model, but EDA primarily foresees what the data can reveal to us beyond formal modeling. 

With EDA you can analyze your data as it is, without the need to make any assumptions. EDA further validates and expands the practice of using graphical methods to explore data. EDA gains insights from statistical theories that give easily decipherable insights. Exploratory data analysis techniques can also be used to derive clues from data sets that are unsuitable for formal statistical analysis.   

Exploratory Data Analysis displays data in such a way that puts your pattern recognizing capabilities to full use. The patterns are evident to an examination that is careful, direct, and most importantly assumption-free. Thus, you can understand relationships among variables, identify problems such as data entry errors, detect the basic data structure, test assumptions, and gain new insights.  

Purpose of Exploratory Data Analysis

The prime purpose of EDA is to study a dataset without making any assumptions. This helps the data analyst to authenticate any assumptions made in devising the problem or operating a particular algorithm. Researchers and analysts can, therefore, recommend new schemes that were not previously considered. 

In other words, you apply inductive reasoning to obtain results. These results may be in opposition to the theories that directed the initial data collection process. Thus, EDA becomes the driver of transformation. This approach allows you to oppose planned analyses and probe assumptions. The ensuing formal analysis can continue with better credibility. EDA techniques have the potential to uncover further information that may open new areas for research.        

Role of EDA in Data Science

We need to understand the role of EDA in the whole process of data science. Once you have all the data, it has to be processed and cleaned before performing EDA. However, after EDA, we may have to repeat the processing and cleaning of data. The cleaned data and results obtained from this iteration are further used for reporting. Thus, using EDA, data scientists can rest assured that the future results would be logical, rightly explained, and relevant to the expected business circumstances. 

EDA helps to clean the feature variables that are to be used for machine learning. Once data scientists get familiarized with the data sets, they may have to go back to feature engineering since the early features may be unable to serve the objective anymore. After completion of the EDA, data scientists obtain a feature set that is required for machine learning. Each dataset is generally explored using multiple techniques. 

Read More: Top 10 Must-Know Machine Learning Algorithms in 2020

Methods of Exploratory Data Analysis

Exploratory data analysis is carried out using methods like:

• Univariate Visualization – This is a simple type of analysis where the data analyzed consists of a single variable. Univariate analysis is mainly used to report the data and trace patterns.
• Bivariate visualization – This type of analysis is used to determine the relationships between two variables and the significance of these relationships.
• Multivariate visualization – When the data sets are more complex, multivariate analysis is used to trace relationships between different fields. It reduces Type I errors. It is, however, unsuitable for small data sets. 
• Dimensionality Reduction – This analysis helps to deduce which parameters contribute to the maximum variation in results and enables fast processing by reducing the volume of data. 

Using these methods, a data scientist can grasp the problem at hand and select appropriate models to corroborate the generated data. After studying the distribution of the data, you can check if there’s and missing data and find ways to cope with it. 

Then comes the outliers. What are your outliers and how are they affecting your model? 

It’s always better to take small steps at a time. So you need to check if you can remove some features and still get the same results. More often than not, companies just venturing into the world of data science and machine learning find that they have a lot of data. But they have no clue how to use that data to generate business value. EDA techniques empower you to ask the right questions. Only specific and defined questions can lead you to the right answers. 

Exploratory Data Analysis: Example with Python

Read More: Why you should migrate to Python 3

 Suppose you have to find the sales trend for an online retailer. 

Your data set consists of features like customer ID, invoice number, stock code, description, quantity, unit price, country, and so on. Before starting, you can do your data preprocessing, that is, checking the outliers, missing values, etc. 

At this point, you can add new features. Suppose you want the total amount. You multiply quantity and unit price to get this feature. Depending on the business requirement, you can choose which features to add. Moving on, by grouping the countries and quantity or total amount together, you can find out which countries have maximum and minimum sales. Using Matplotlib, seaborn, or pandas data frame you can visually display this data. Next, by grouping the year and total amount, you can find out the sales trend for the given number of years. You can also do the same for each month and find you out which time of the year has shown a spike or drop in sales. Using this same method, you can identify further problems and find out ways to fix them. 

Read More: How to Use Data Analytics to Improve Enterprise Sales Numbers

The key to exploratory data analysis is to first understand the LOB and get a good hang of the data to get the desired answers. Get in touch with us to know more about EDA. 

COVID-19 Gives A Fillip To Innovative Digital Retail Tech & E-Commerce

Containment measures implemented as a result of COVID-19 have created a “hide and seek” situation for the retailers and their customers. Although many believe that this is forcing retail tech to evolve, it is in fact doing much more. It is causing a ‘retail revolution’ and significantly changing the retail tech across categories. This article will discuss how COVID-19 will advance innovation in Retail technology. 

Five Essential Retail Technologies

One way in which the COVID-19 pandemic has forced the retail industry to adapt to the “New Normal” is by finding viable ways to ensure business continuity. Home quarantines and mandated store closures around the world have expedited the shift to online shopping, forcing many organizations to adopt e-commerce as their primary shopping channel. 

Here are five essential approaches to retail tech across categories in response to the current crisis:

1. Work from home capabilities

With over 210 countries affected by the coronavirus as of May 2020, several countries have encouraged or even enforced work from home (WFH) as the only viable option for business continuity. This requires a shift in work dynamics necessitating companies to become more flexible and open up communication lines across departments and customers. Retail organizations will have to adopt technology enablers and digitize their processes and workflow to bolster WFH capabilities.

2. Integrated inventory management 

Paranoia about supply shortage has customers adding multiple items to their cart at various stores, but this does not always lead to a purchase. This has led to uncertain stock demand, which causes fluctuations in the stock condition, making it extremely challenging to regulate and maintain inventory during this crisis. 

Retailers thus need to focus all their efforts on preparing for a flexible, streamlined, and digitally backed omnichannel retail strategy with an enterprise-wide centralized inventory management system if they want to stay profitable. With an integrated omnichannel approach, you can deliver a unified experience to your customers across channels by tracking, refreshing, and refilling inventory quickly. 

Read More: How a Smart Product Ordering System Helps Retailers and Wholesalers

3. Go digital!

Though the shift to digital in retail has always been in the cards, the pandemic is fast-tracking this move, allowing retailers no room for delays in adopting a digital-first approach. 

According to a survey held by YouGov in March 2020, 83% of internet users in Hong Kong and 85% of those in China said they avoided crowded public places. If the outbreak of COVID-19 worsens, 58% of US internet users said that they would avoid shopping centers and malls. If retailers do not prepare for these new purchasing behaviors, they will fall behind other competitors in the market. 

Read More: Ways to Leverage Smart IT Solutions for your Retail Business

4. Smart delivery

Delivery is quickly becoming the only option for most retailers. However, there are risks associated with it. While a shopper may be anxious about accepting a parcel in person, a driver or delivery person is also at the significant risk of coming in contact with an infected person, and he in turn might infect other customers. This situation makes it imperative to scale up a contactless delivery program. 

Retailers can use apps that allow them to track the driver’s location in real-time and ensure that they are learning the routes and delivering packages to the right locations. It is extremely important to get started on this immediately to stay competitive. Leverage the educational capabilities of an app to help onboard new delivery drivers quickly. 

Retailers need to invest in:

• Finding reliable logistics partners
• Automating logistics and supply chains for real-time updates 
• Finding innovative ways to meet the customers’ expectations

5. Adopt “self-server” technology

PYMNTS.com reports that the projected value of the mPOS terminals market by 2024 is $55 billion.

Retailers need to focus their resources on implementing better hygiene measures and shelf replenishment than asking the staff to keep their scanners clean. Technological development is now allowing the shopper to scan and pack their items as they shop. This self-serve capability in the form of an app can be downloaded on to the personal devices of the customers. It allows them to shop for essential items and put them into their own bags and pay for them at a special counter before they leave. This results in less interaction with other customers or staff and less waiting time for payment. 

Read more: How Important is Technology in Retail: 4 Focus Areas

Advance Innovation in Retail Tech

The COVID-19 pandemic has disrupted the retail sector, altered consumer behavior, and brought in lasting changes to the retail landscape. But success depends on your response to the COVID-19 situation. On the bright side, it has forced many retailers to adopt innovation in retail tech. 

According to PYMNTS.com, “one hundred fifty million US consumers are expected to use in-store mobile payments by 2021.” Retailers will adopt contactless technologies such as QR codes, mobile payments, and tap and go, and this revolution is happening as we speak. The time to strike is now. Give us a call and let’s discuss how to get you started. 

Why Business Process Re-engineering is a Must-Have for Organizations

COVID-19 has knocked down businesses around the world. On the one hand, it had employees scrambling for cover as soon as the lockdown was announced, while on the other hand the ensuing panic substantially increased consumer demand. This has necessitated a huge shift in the way organizations manage their business. At this critical time, Business Process Re-Engineering (BPR) can assist organizations in maximizing customer value while minimizing the consumption of resources. Let us now discuss how BPR can help your organization handle a crisis like COVID-19.

What is Business Process Re-Engineering?

Business Jargons defines Business Process Re-engineering as the “analysis and redesign of core business processes to achieve substantial improvements in terms of performance, productivity, and quality.”

The crisis of COVID-19 is completely changing the business world and BPR can create drastic improvements and help organizations to free themselves from conventional approaches. BPR focuses on improving organizational operations enterprise-wide. 

Related Reading: How Automation Ensures Businesses Stay Afloat During COVID-19 Crisis

Seven Amazing Benefits of Pre-Planned BPR

BPR is an important method that allows enterprises to revamp existing business processes to improve productivity, quality, and cycle time, especially during a crisis.

1. Outstanding customer satisfaction

 “The customers’ perception is your reality.” – Kate Zabriskie, President, Business Training Works, Inc.

Panic driven buying has changed the customers’ needs. During this time, matching your organization’s services with customer expectations allows your business to build lifetime loyalties with your customers. BPR enables your enterprise to achieve this by re-designing your business process.

BPR strategically plans relevant activities to design, manufacture, and market a product that provides customer value. It analyzes value-creating activities and compares it with your organization’s competitors to find better ways to satisfy your customers.

2. HR management and health monitoring

All enterprises are concerned about the health, safety, and wellbeing of their employees. Post COVID-19, proactive management of employee health will include collecting important information and using it for health management. BPR can help the organization undertake major changes in the attendance recording system including mandatory temperature checks at workplaces. Large organizations will benefit from enhanced HRMS software to include such data, minimizing the risk of disease spread and work suspension.

Related Reading: SAP Payroll Compliance: Extending Support During COVID-19

3. Enhanced security features for remote working

Apart from the IT industry, COVID-19 has introduced the concept of remote working for several other organizations. BPR ensures that this phenomenon receives a review of security policies, network management, acceptable use of software, and connectivity. Without infringing on its privacy policy, an organization will be able to monitor employee productivity.

4. Keep-up with the radical change in supply management

As global trade is under restrictions due to health, geopolitical and economic concerns, supply management will have to undergo a phenomenal change. This would include quality management, supplier collaboration, warehouse and logistics management, spare parts management, and shipment tracking. BPR will help your enterprise find scalable and adaptable solutions as your business experiences rapid changes in demand and complexity.

5. Skilled service operations

COVID-19 has created a reduced dependence on human travel and physical presence bringing in a massive change in service management. Organizations will have to increasingly rely on IoT and AI for remote monitoring operations, fault detection, and auto-correction. With BPR optimization, enterprises will be able to re-design highly complicated and skilled service operations resulting in much higher productivity and less reliance on service experts.

6. Digital signatures

Thus far, digital signatures and validations have been adopted for compliance or security checks. But now, constraints on the handling of printed documents and remote working have necessitated increased use of digital signatures. Optimization of BPR will help bring in process and software alignment across the organization ensuring security while overcoming the hurdles involved.

7. Lower commercial space requirement

The transition to remote working will drastically reduce the need for commercial space. If your organization wants to bring about this change, there would be substantial value generation for your stakeholders. This could result in reduced rental expenses and increased free spaces. BPR optimization in seat utilization could bring higher productivity. The rostering and office locations of the employees could be done in a way that maximizes space utilization. 

Related Reading: Optimize Workforce Management with SAP SuccessFactors and Qualtrics

Use BPR Optimization to Handle Any Future Crisis 

No one knows what the future will bring. But we can learn from the COVID-19 crisis and act smarter and strengthen the global supply chain by benefiting from Business Process Re-engineering. BPR optimization can revamp your organization to leverage the power of AI and other emerging technologies equipping you to maintain business continuity amid uncertainty and disruption. 

BPR will help you reassess your sourcing strategy and rebuild your supplier network. Your organization will be able to find the balance between the level of risk you can accommodate and the amount of operational flexibility you want to achieve. 

Working from home would require a huge emotional and cultural shift. Hence, this is the time for enterprises to revisit your strategies. There is a huge value in optimizing BPR to make the shift now so that you and your employees can look towards the future with a smile on your face. With all these benefits in store, why wait to get started on BPR? Give us a call and let’s discuss how we can get this working for you. 

SAP Commerce Cloud: The Path to Delivering an Omnichannel Experience

The accessibility of the internet and various commerce solutions have broken boundaries to open up a global market. As a result, many businesses are looking for e-commerce solutions that are flexible, scalable, and provide highly targeted customer experiences across multiple touchpoints. Enter- SAP Commerce Cloud (formerly known as SAP Hybris Commerce).

What is SAP Commerce Cloud

SAP Commerce Cloud connects the dots in a comprehensive commerce portfolio integrating all digital and physical activities of the customer, creating a smoother and more personalized shopping experience. SAP Commerce Cloud is one of the five key components of the SAP C/4 HANA suite. SAP Commerce Cloud, together with SAP Marketing Cloud, SAP Sales Cloud, SAP Service Cloud, and SAP Customer Data Cloud form the entire CRM environment. 

SAP Hybris Commerce was renamed to SAP Commerce Cloud since SAP shifted their technology from proprietary infrastructure to the cloud. SAP Commerce Cloud uses an open-source Kubernetes technology and runs on the Microsoft Azure Hyperscale platform.

Features of SAP Commerce Cloud

• Omni-channel Storefront – gives your customers a consistent view of your contents or end-products across all their devices – PC, smartphones, or tablets. Today, customers interact with a brand both online and offline before considering to purchase an item. 
• Personalization –  You can improve the average order value and augment gains by providing tailored content, based on the shopper’s behavior and buying history. SAP Commerce Cloud allows you to segment customers and provides relevant product recommendations based on preferences. 
• Order Management – Managing global market channels lead to complexities, data fragmentation, and high costs, making order management a challenge for companies. SAP Commerce Cloud solutions can support any B2B, B2C, or B2B2C go-to-market strategy through a single commerce platform and simplify the process. You can have a single view of inventory, shipping, and returns throughout the organization thus streamlining order management. Customers can have complete flexibility without cluttering stock levels.
• Real-time Customer Support – The Assisted Service mode in Cloud Commerce helps you offer real-time sales support from your business website directly. If the customer gets stuck during an online purchase or needs help at a retail store, the Assisted Service mode immediately connects them to customer support to help them complete their purchase or answer questions. The customer service representatives get a complete view of the profile of the customer complete with their purchase history, preferences, and so on.
• Accelerators – The SAP Commerce Cloud provides industry accelerators that can address the unique requirements of your industry. SAP Commerce Cloud offers cross-industry accelerators for B2C and B2B sectors, accelerators that are specific to the Chinese market, and several specific accelerators for Telco and media, financial services, travel, and citizen engagement. 

Related Reading: SAP Preconfigured Solutions Boost Efficiency Among Industries

Integrations offered by SAP Commerce Cloud

In order to ensure the best customer experience, your commerce solution needs to be integrated with the other solutions in your ecosystem. While this can be complex and time-consuming, the prebuilt integrations offered by SAP Commerce Cloud help simplify and unlock efficiencies of this process. SAP Cloud Platform Integration service eases integration by using publicly available APIs and by using industry-standard protocols for managing data transfer. 

Related Reading: SAP Focused Industry Templates & Automation Solutions

SAP Commerce Cloud offers pre-built integrations with SAP S/4 HANA, SAP Marketing Cloud, SAP Service Cloud, SAP Customer Data Cloud, and SAP Sales Cloud portfolios, services from third-party providers, and various other solutions. These pre-built integrations permit end-to-end process management with the SAP Cloud Platform. SAP Cloud Platform integrates the master data with business processes to create a single source of truth. It thus prevents the complexities arising due to siloed data. What’s more, the intuitive user interface gives control to your system administrators to manage data with transparency.

Related Reading: SAP S/4HANA: Redefining End-To-End Solution

Benefits of SAP Commerce Cloud

• Rapid onboarding by providing quick access to development, staging, and production environments 
• Many self-service features that give you the power to control the working of your commerce solutions in the cloud.
• With the cloud-native capabilities, you also gain access to the latest releases and upgrade packages, code checks, and quality gates.
• The SAP Cloud Platform Extension Factory allows extension and integration of microservices without affecting the core application
• You can augment your market reach and organize data through marketplaces, search, social, and marketing channels.
• The platform is highly scalable and can easily handle your traffic peaks. In other words, it grows with your business. 
• You get automatic weekly full database backups and hourly incremental backups.

The SAP Commerce Cloud is a hyper scalable, flexible, and high-speed omnichannel commerce solution that is delivered through a SaaS model. You can exploit the efficiency and speed of the cloud by using SAP’s shared cloud infrastructure. You end up having nominal IT costs, you don’t have to maintain servers, and to top it all you have the world-class data security that SAP provides. So why not make the move (if not already done)? Fingent can help streamline last-mile delivery and improve a number of business processes. Our team of specialists can help you successfully deploy SAP Commerce Cloud and become a truly global digital business. Contact us today.