TDWI | Training & Research | Business Intelligence, Analytics, Big Data, Data Warehousing

Data Trends to Watch in 2020

From ETL to CCPA, how your enterprise manages data will continue to evolve in 2020. Manage Engine’s Rajesh Ganesan and Actian’s Jack Mardack explain.

• By James E. Powell
• January 3, 2020

Getting the most value from your data means working with data that’s ready for analytics. Often, data from new sources needs to be prepared or transformed before you can incorporate it into existing analytics.

For Further Reading: How to Survive the Coming Data Privacy Tsunami Strategy and Your IT Archetype Calculating Your ETL ROI

Rajesh Ganesan, VP at ManageEngine, notes how the importance of manipulating data will rise in 2020. “Data analytics has seen a huge transformation in the past decade. Moving into 2020, instead of data analysts running complex analytics and structuring data, augmented analytics are set to change the way data is processed.

"Augmented analytics will employ capabilities of AI and machine learning to automatically process data quickly and efficiently, cutting down the time it takes to transform data into insight. This means analysts will get to spend more time on data analysis rather than spending time preparing the data for analysis."

Improving data's usefulness will also help spread the use of analytics throughout an enterprise. Ganesan points out that "democratization of data has opened up analytics use to departments that have traditionally not employed analytics for decision making -- such as IT. This means that there are now new and different sources of data that need to be standardized and checked for quality before they can be used for analysis.

"To accommodate this, next year is going to see a rise in the demand for ETL (extract, transform, and load) tools, which help reduce the time it takes to standardize data. Analysts will need to begin familiarizing themselves with newer sources of data and employ ETL tools when necessary."

Jack Mardack, VP at Actian, echoes this trend, especially the use of new transformation tools.

"The democratization of access to data is having a major impact on data management. In 2020, this democratization of access to insights will extend to other parts of the analytics stack. The low-code/no-code movement has come to many areas and functions that historically supported analytics, such as data integration and ETL tools. The provisioning of analytics databases is much easier and far less demanding of traditional technical skills. The proliferation of easy-to-use interfaces combined with the instant availability of cloud-based services is also driving change for IT personnel."

Of course, with so much more data available, IT will need to focus on performance. Mardack says that to support the intense demands of new analytics use cases at scale, IT practitioners will look to "up-level" their data warehouse capabilities for absolute throughput performance. "IT will frequently look for hybrid solutions that make it easy to connect and operationalize analytics wherever data lives -- in the cloud or on premises (which, for some industries, may be due to data subject to regulatory requirements or the organization simply isn't comfortable hosting it in the cloud). We'll also see an explosion in enterprises using data warehouses to easily connect diverse data sources to hybrid and multicloud environments."

That will be especially true as data collection will increasingly occur in real time. "Over the past few years we've seen the focus of data management shift from reporting and analysis of historical events to driving business operations and customer/user experience (CX) in real time. In 2020 we're going to see many more enterprises start using real-time data to drive customized user experience at scale. In both B2B and B2C scenarios, we're going to continue to see the rise of hyper-personalization, customer 360, and contextual communications use cases to drive better CX."

What data is available will be limited by new data regulations, including the upcoming California Consumer Privacy Act (CCPA) which went into effect January 1 (although enforcement won't begin until July). Ganesan explains that more countries are following the European Union's lead by implementing data protection laws similar to the GDPR, such as Thailand's Personal Data Protection Act (PDPA), which goes into effect in May 2020.

"In 2020," he says, "data analysts will need to stay abreast of changes to local and international data protection laws by working closely with compliance teams and firms to handle personally identifiable information with care. With increased awareness of and emphasis on data protection, analytics tools will shift to focus on protecting the privacy and security of users' personal data."