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Make quicker, smarter decisions by democratizing your data

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By Piyush Agarwal, SE Leader, India, Cloudera

In the past year or so, we have witnessed unprecedented changes in terms of how we conduct our businesses and personal lives. Across industries, adapting to changes in this volatile market has been crucial to build an agile and resilient business model. Here is where data has played a big role. Businesses have realized the need for data and real-time analytics now more than ever, not just in terms of survival but to thrive and ensure business continuity. It shouldn’t come as a surprise, therefore, that a recent report by IDC suggests that Indian enterprises are investing heavily in big data technology and the spend on such solutions is poised to grow at a five-year CAGR of 14.6 per cent over the forecast period of 2020-25.

A major pain point for organizations continues to be around limited access to data and its analysis in real-time. This, combined with the exponential growth of connected devices as well as the limited number of data analysts and scientists, has made getting the full value of their data an uphill task for businesses. That’s why an enterprise data strategy is the need of the hour. It helps businesses address these issues by adopting a more holistic approach to their data. The strategy needs to be relevant, practical, and agile – one that can be applied across business processes, regardless of location, function, or business unit.

Easy navigation of data with effective management
The world underwent a tectonic shift with respect to the adoption of technology and digitization. A recent report suggested that between 2020 and 2021 alone, the number of internet users in India increased by 47 million. This led to a data boom! And organizations needed to find ways to effectively manage this data, which can be a rather challenging and daunting task. That is why it is essential to have a robust data management platform that can handle large amounts of data securely and efficiently. With an enterprise data cloud in place, businesses no longer have to worry about having data across multiple cloud and on-premise environments as the enterprise data cloud connects and manages data workflows across different environments. It will also support various analytic functions, from streaming and big data ingestion to the Internet of Things (IoT) and machine learning. This way, businesses will be able to get the most out of their data.

In addition, businesses also tend to have disparate information systems from several different vendors. Therefore, a good enterprise data cloud should provide interoperability, integrating various solutions into a single, easy-to-use, and readily accessible platform, while maintaining security and governance.

Laying the groundwork for data democratization

It is crucial for businesses, especially in today’s digital world, to be able to maximize the value of their data. And democratization can be one of the first steps that they can take to tackle some of the common problems faced. With data now being at the center of all decision-making processes across various industries like manufacturing, telecom, retail, and healthcare, among several others, this is something that should no longer be considered an option, but a necessity. In fact, in Cloudera’s recent enterprise data maturity report, all of the surveyed senior business decision makers (SDMs) in India reported that they need data in real-time, or at least near real-time to make business critical decisions.

Take telecom for instance. An industry that has traditionally focused on voice services, is now coping with an increased growth in demand for data services. Last year, a study by Nokia revealed that data traffic in India saw an unprecedented growth of 60x in the past 5 years. The large-scale digitization that the world continues to undergo will only increase this growth exponentially, with the industry having to grapple with data storage and analysis challenges. Similarly, with IoT becoming more commonplace in the manufacturing and healthcare sectors, it also faces the challenge of having to store and analyze growing amounts of data generated by interconnected devices and platforms.

Now, imagine if all the data generated by all these numerous platforms could be properly managed and quickly and efficiently analyzed. Organizations would be able to make informed decisions at a much faster pace, aligning with real-time trends and changing market landscapes, ensuring their decisions are relevant from a business standpoint. Benefits can come in the form of business or operational improvements such as increased operational efficiencies, resilience, and cost savings.

One of the barriers to data democracy is, ironically, organizational structure. More often than not, organizations tend to have a specific team that looks after the analysis of the data and churns out insights based on the business, making it a long-drawn process for other teams to gather the required information. And the data is oftentimes kept in silos, which makes it time consuming for the analyst teams to extract and consolidate the relevant data, delaying the decision making process. By not restricting the data to silos, other teams can access the data, empowering them to make quick, data-driven decisions.

While a change in this structure would help speed up the process, providing data to a non-technical employee who is unsure of how to interpret or understand the data, may lead them to be hesitant to use that data. In such a scenario, having reliable data management platforms and tools that are easy to use would go a long way to push more non-technical staff to extract, analyze, and use the data independently and more confidently.

Some compelling features include:

Self-service data analytics. With easy-to-use features such as natural language query and visual data discovery, users are able to perform complex data analysis, visualize their data, and generate reports on their own with nominal support from the data analysis team. Time and resources can then be dedicated to gleaning insights and analysis instead of constructing and maintaining systems.

Low-code and no-code tools. Advances in technology have allowed for tools that help end users and non-technical professionals build machine learning models using user-friendly features and drag-and-drop modules. This will speed up software delivery since end users do not need to rely on data scientists’ help. Take the retail industry, for example. Leveraging a customer’s purchase history, salespeople can use a no-code platform to quickly build a machine learning-based tool which can suggest relevant products to upsell and cross-sell.

Data privacy, governance, and security. Implementing the right policies to maintain strict enterprise data privacy, governance, and security across all environments is also extremely crucial.

Once companies have put suitable tools in place, then comes the next crucial step – training the users. We’ve discussed how self-service data analytics forms the backbone of data democratization. Hence, it is imperative for businesses to ensure that users are familiar with the tools and processes to maximize the data that is made available. Furthermore, without the ability to access data points comfortably, users will not be able to generate useful insights even if the tools and data are at their disposal.

We’re seeing many larger organizations transition to hybrid environments for their IT infrastructure. Amidst this, employees will find it tough to learn every Application Programming Interface (API) to access the required information. Where speed is of the essence, one of the best ways to approach data democratization is to employ an enterprise data cloud that works across all major public clouds and the private cloud. It can be integrated with multiple architectures and provides big data management and analytic experiences across the data lifecycle.

The bottom line is this – data is almost a limitless resource, but it all boils down to what we make of it. Amidst the immense digital transformation we’re witnessing across the country, how businesses are able to extract the full value from data will be what sets them apart. By empowering their workforce with the access and tools to realize the full potential of data, businesses will accelerate decision making and open their doors to newer opportunities and horizons.

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