Skip to main content

How the modern data stack will transform in 2021 and beyond

How the modern data stack will transform in 2021 and beyond
(Image credit: Image Credit: Wichy / Shutterstock)

After a year of unforeseen events and a decade’s worth of technology innovation, it may seem almost impossible to imagine what 2021 holds. Most businesses have encountered first hand how data has enabled them to make better decisions, whilst also experiencing the modern data stack’s full potential of enabling them to move quickly. In an unprecedented working environment, organizations saw the importance of having the right technologies, tools, and processes in place to make data analytics available, accessible and understandable.

So, what are the key areas which will transform the modern data stack this year? And what opportunities do these present for businesses?

Think beyond the dashboard and open up data experiences

Traditional dashboards have been a great starting point to data analytics for many organizations over the years. However, the demand for real-time insights is highlighting the limitations of these types of dashboards for modern enterprises. Instead, organizations should consider new data experiences that go beyond traditional charts and graphs.

For businesses, that are now heavily reliant on real-time data to better serve attention-poor customers and streamline their operations, immersing real-time data into workflows is key to staying competitive. With this in mind, embedded analytics and data insights are predicted to transform business intelligence (BI) in 2021 and beyond.

AI-augmented analytics, in particular, will continue to gain significant traction this year as business users increasingly require easy ways to find the data they need. For example, for online streaming services - where the competition is high for viewer time - it’s crucial that data analysts have access to the business’ real-time streaming analytics. As data is steaming from various sources including household demographics, content that has been viewed, it can be difficult to understand where to get started. Augmented data workflows enable analysts from being a data bottleneck to facilitating rapid data discovery across an organization.

Another example is AI solutions such as chatbots that will enable employees to easily ask questions about their data without disrupting their workflow, enabling them to interact more freely with the data and save time.

Data products will be available for internal teams

Not only are companies building data products for consumers, but they are also starting to build products specifically for internal data. Consumer data products like Rightmove or ASOS - where a consumer types in a query and they will receive data related to their search criteria such as a list of products or properties - are now commonplace. However, data products for companies haven’t been developed in the same way. Instead, employees often find themselves searching through static spreadsheets and pivot tables to get answers to their questions. This can be a time-consuming and frustrating task for the employee, especially if they need the data immediately.

Yet the tide is turning and 2021 will see an increase in internal data products for modern employees that are tailored to specific job roles and needs. With easy-to-use data and AI or Machine Learning (ML) technology, solutions like these have made it possible to bring data analytics accessible to everyone and not only teams with specialized knowledge and training. One of the best examples we’ve seen this year is a touch-enabled interface created specifically for employees to view metrics about streaming service titles. Using a product experience to democratize data internally will only become more common as businesses continue on the path towards automated, insight-led decisions.

Data lakes will look more like databases

One of the key changes we will begin to see this year is that data lakes will start to resemble normal databases. IDC estimates that 80 per cent of worldwide data will be unstructured within the next five years. As this trend continues to grow, so will the pressure to store and manage data in a way which will allow businesses to easily access and analyze it, and then turn it into tangible results.

As on-premises data lakes begin to migrate to the cloud, this year we’ll also see them starting to take on crucial data warehouse functionality, making it easier to query datasets. Not only will this be more cost-effective, but employees will also be able to stream and access data in real-time, share insightful reports with ease, whilst relying on the platform's trusted and robust security. Multi-cloud data warehouses are built to handle data of all shapes and sizes, ranging from spreadsheets to petabytes of data. It also supports Structured Query Language (SQL) queries, making it simple to use as any other basic database. This isn’t the only shift to data lakes looking more like databases, other functionalities such as transactional consistency, rollbacks, and time travel will also take shape within data lakes this year.

There’s no denying that we have seen the use of data become even more important in the last year. This year will be no different, especially as businesses begin to rethink their business strategies for a post-pandemic age. We’ll expect to see new rich, AI-driven experiences, internal data products for employees and data lakes taking a new form. One thing’s for sure - 2021 promises to be another big year for data.

  • Colin Zima, Chief Analytics Officer and VP of Product, Looker at Google Cloud.
Colin Zima

Colin Zima is Chief Analytics Officer and VP of Product at Looker, Google Cloud.