Big Data’s Big Outlook


Businesses and organizations all over the globe have made big data management and analytics much more strategic over the last few years. This has been fueled by digital transformation initiatives, leveraging data for competitive advantage and even towards monetizing data assets.

Following the early starts to the 2020s and the effects of the pandemic and the economic breakdown caused by it, Businesses are keen to adopt better ways to utilise their data to manage supply chains and retain employees. With the onset of major cybersecurity incidents around the world, the drive to step up data governance operations has become a major priority.

For 2022, the outlook is strong on changing how businesses collect, manage, utilise and analyze growing sets of data.

Multiple Clouds

Organizations are expanding their use in storing data into multiple cloud platforms such as Snowflake, Microsoft Azure and Amazon Web Services – even creating networks that distribute the data storage across the multiple clouds.

Bustiness analytics can become challenging when the data is spread across a mixture of multi-cloud platforms and on-premises, which is heading for a unified view of the various data courtesy of new software tools such as Starburst Galaxy, Qlik Forts and others, making the collection of all data in the various areas available for access for data analytics tasks.

Being able to access dispersed data with business intelligence tools is this year’s viable alternative to the traditional way of collecting data from various sources and managing it in a central location.

Predictive and Prescriptive

Data analytics is traditionally used to understand what has happened, but today it is being used more and more to predict what will happen and collate suggested prescriptive responses and automated actions towards the analytical results. This in turn makes the data a more actionable asset.

This shift has been driven by the growing availability and adoption of easy-to-use machine learning tools by data scientists and analysts. This has provided them with the ability to manage and deploy at scale machine learning features with next-generation feature stores, along with a new generation of distributed frameworks for training and deployment.

Frequent releases of machine learning tools and libraries are among the main factors, along with consolidated platforms such as Snowflake that close the gap between analytics and machine learning.

Data Governing

Data managers previously have had to rely on point products and tools to automate data governance processes. This has made it a challenge to protect the data against unauthorised access and misuse.

2022 has seen many businesses and organizations combine these tools and capabilities into more comprehensive data governance platforms such as Collibra, Informatica and Talend among others. Data managers are looking forward to 2022 adopting and implementing platforms such as these to improve data governance efforts.

It is a big year for big data. For more information on any upcoming data analytics conference and updates on big data analytics trends, check out the upcoming events from Whitehall Media.