Data is not new. Remember the time (not so long ago) when enterprises poured over precious numbers on spreadsheets to decipher the big picture? Then came statistical analysis, data mining and data science.

The deluge of data started with the growing popularity of Facebook, YouTube and other online services. Soon, the advent of Internet of Things (IoT) and machine learning (ML) paved the way for the world of big data. By 2025, the volume of data created in the world will top 163 zettabytes (ZB) as predicted by International Data Corporation (IDC)!

Decoding Big Data

Gartner defines big data as “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” For Forrester, big data entails “techniques and technologies that make handling data at extreme scale affordable”.

In other words, the data sets are too large and complex for traditional data processing software programs to manage. However, that isn’t deterring organizations from turning to big data. Companies like Netflix are using big data to anticipate customer demand while enterprises in the manufacturing space are reinventing themselves to enter the digital space through big data.

Numerous factors have been responsible for the big data revolution – right from the growing amount of digital data at our disposal to affordable data storage solutions and advanced computers that aid better business analytics. From predictive maintenance and enhanced customer experience to fraud prevention and operational efficiency, big data enables new-age enterprises to reap myriad benefits.

Read more: Rundown of the Most Popular Big Data Platforms

Finding Value 

While it is true that a real-time aggregated data repository can help drive the decision-making process while optimizing business processes and customer relationship management, the fact remains that many businesses fail to achieve it. The focus needs to shift from the sheer volume of big data (and storage issues) to finding value from data.

Data has its own intrinsic value. But when businesses fail to discover it, they lose their much deserved competitive advantage of owning data. To get more actionable insights in real-time, enterprises cannot afford to have data in silos. Data needs to flow easily and fluidly across the enterprise, enabling analysts to recognize patterns and predict behaviors. There has to be a sound value proposition to the data collected, processed and stored in any organization.

Role Of Data Platforms 

A good data platform, unlike traditional data warehouses, helps discover the value in data. It assists enterprises to draw actionable insights and business intelligence (BI) to make better data-driven decisions in real time, irrespective of the volume, variety and velocity of the data. It is not just about aggregating unstructured data, but also about the ease of access to the right data for the right purpose at the right time.

As a central hub for data flows and information leverage, data platforms help organizations deliver fast, personalized and optimized processes. Further, open-source frameworks such as Hadoop and Spark make big data easier to work with and economical to store.

Earlier this month, two of the biggest data management platforms, Cloudera and Hortonworks, announced their “all-stock merger of equals”. This development, experts believe, will raise the bar on innovation in the big data space, especially in supporting complex and larger big data initiatives in a hybrid environment.

Continuous optimization is the name of the game. It is not just enough to collect, aggregate and store the data; data needs to be constantly updated. To derive maximum benefits, enterprises need to start addressing the operational problems with dedicated strategy in place. Investment in resources – people, technology and time – is essential to make the most of data in terms of business optimization.

Going Forward 

According to IDC, the revenues for big data and business analytics (BDA) solutions will reach $260 billion in 2022 worldwide. BDA revenues are expected to total $166 billion this year, an increase of 11.7% from previous year.

There’s no denying that keeping up with big data technology is an ongoing challenge. For data-driven, outcome-focused enterprises, an important step is to determine which big data platform is the best fit for their unique business needs. They need to look at big data as an integral extension of the company’s information architecture.

To gain competitive edge in a world where physical and digital spaces converge seamlessly, enterprises will need to invest in the right combination of latest technology and skill sets. The biggest challenge – and opportunity – is to extract maximum value from big data to improve operations in real-time, create more personal customer experiences, and empower enterprises to drive innovation. Is your business ready for this digital transformation? Talk to our expert team.

Read: How to Integrate Data for Digital Transformation Success

16 Oct 2018
Author : Jisha Krishnan