Data analytics is changing – Are enterprises ready?

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Data Analytics is changing  Is your enterprise ready - Data analytics is changing - Are enterprises ready?Data and analytics continue to be a top investment priority for business and technology leaders in 2020, with close to 70 percent of global enterprises planning to increase their analytics spending this year. Certainly a good news for everyone in the data domain–it’s just that the analytics scenario within organizations is not going to be very simple going forward.

A large part of the existing analytics and data projects are quite big in size and scope, while being highly ambitious about results. But, if we probe deeper, we will see a different picture.

According to Gartner’s last year estimation, almost 80 percent of analytics insights will not deliver business outcomes through 2022 and about the same number of AI projects will likely not go beyond the experimentation phase this year.

What has gone wrong? The answer isn’t necessarily provided by technology. Very clearly, organizations need to adapt to the changing ecosystem of data in the coming days and prepare to convert the growing amount of data into an opportunity rather than a problem.

That isn’t going to be very easy.

The mounting challenge called data

There are a number of reasons behind failed data projects –siloed approach, lack of vision, skills gap and many more. But one of the biggest challenges that organizations face today is the explosion of data, leading to massive pressure on organizations due to space crunch and the inability to store data for effective analysis. To add to this stress, unstructured data is growing at an unprecedented rate. Consider the case of IoT for instance.

IDC estimates that there will be 41.6 billion connected IoT devices, generating nearly 80 ZB of data in 2025! This is certainly huge and presents a massive challenge for organizations. Bulk of this data will be generated by video surveillance applications, while industrial and medical devices will add to the growth.

This is in addition to the traditional sources of unstructured data like text documents, voice recordings, videos and social media posts. In fact, as much as 80 percent of the enterprise data is unstructured. Connected systems and devices are going to be inevitable components of organizations’ digital transformation journey and so is the growth of unstructured data.

Converting this growing data sets into real business insights will perhaps be the greatest undertaking for organizations in the new decade.

The scale-up conundrum

Often while working with large data sets, traditional approaches and legacy systems come in the way of arriving at the desired results. These approaches will likely shift in 2020, because data sources are now highly scattered, and new applications are emerging —be it behaviour analysis or fraud prevention or real-time edge analytics.

As the volumes of data go up, will the existing systems be able to manage and scale up? How will the present technologies and systems work on the ever-growing unstructured data sets? These are some critical questions that need answers in 2020.

For some of these answers, organizations seem to be turning to the Public cloud, which is emerging as the de-facto standard for storing and processing vast amounts of data. Cloud-based analytics effectively addresses some of the critical challenges like storage, scalability and elasticity for enterprises, whole also ensuring tighter integrations and centralization of data lakes. Most importantly, organizations do not have to worry about the future data growth and unanticipated demand on a cloud model.

The trend in the market is quite clear today. Organizations that are on the verge of starting an analytics journey are already considering a cloud-first deployment. And those with existing on-premise systems are going for a hybrid deployment model rather than mere capacity extension.

Conclusion:

As organizations look at supercharging their data and analytics projects with AI, cloud will prove to be a strategic investment for most organizations this year.

Cloud is predicted to change the whole data dynamics in the coming days. The fate of a data analytics project –whether it’s going to be a grand success or will fall flat—will depend largely on how effectively cloud fits into the whole equation.

By Amit Gupta, Co-Founder & CEO, Rapyder Cloud Solutions.

[Read Next: How To Build A Cloud Strategy For Your Company]


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Amit Gupta is the Co-Founder & CEO, Rapyder Cloud Solutions. He has over 20 years of experience in delivering strategic projects in big data and highly responsive systems. He has headed a business unit of hospitality automation tool and touched 4000+ customers, successfully selling it before founding Intelligentia.

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