2020 was a year of rapid and tumultuous change for nearly every business – especially in the cloud. Our need to work 100 percent remotely, and our need to have data accessible to us no matter where we worked, accelerated the move to the cloud for many organizations. We’re likely to see that trend continuing into 2021 as many organizations decide that the remote way of work and sharing information via virtual channels is part of the new normal.
But along with organizations speeding up a move to the cloud, we’re seeing another long awaited macro trend picking up momentum: More widespread use of advanced analytics such as machine learning (ML) and artificial intellligence (AI) in the cloud. In 2021, both ML and AI will play a bigger role in helping data teams move faster in the cloud and improve access to data. Here are two ways we see ML and AI trending in the cloud in 2021
1. Machine learning and artificial intelligence come to the cloud data warehouse
The major cloud data platforms – Snowflake, Amazon Redshift, Google BigQuery, Microsoft Azure Synapse, and Delta Lake on Databricks – are all adding ML and AI functionality. As a result, users can take advantage of advanced analytics using a few simple SQL codes.
This shift is part of a larger trend toward a convergence of cloud data warehouses and data lakes into a more integrated data platform. Imagine a future where people don’t actually care where their data lives.
Cloud data warehouses can hold unstructured data and data lakes are beginning to support ACID compliance (atomicity, consistency, isolation and durability) for more of a cloud data warehouse type product.
Databricks has come up with the concept of the Lakehouse, which combines the best of data warehouse and data lake technology. Enterprises no longer have to maintain distinct data lakes and cloud data warehouses. All of your data just goes into one storage layer, and you build all of the functionality on top of that storage layer. We expect to see this type of convergence continuing over the next year.
2. Advanced analytics in data governance
Data governance has never been more important. Data teams need to make sure that the right data is being accessed by the right resources, for the right reason. Now they’re getting help – from advanced analytics.
Some companies are using AI to classify datasets and determine who should have access to them in various roles and routines. Others are beginning to sophisticated ML to scan the enterprises entire datasphere for sensitive data and potential security risks.
These solutions can identify Personally Identifiable Information (PII), GDPR data, passcodes and passkeys, and map all of the potentially sensitive data across an organization on a single dashboard. Many solutions also support more passive approaches, like manually loading data for scanning. But the real value lies in harnessing these ML solutions to actively, automatically scan and protect data as it enters the organization. Expect these solutions to mature in the next year, and more of them to pop up on the horizon.
Learn more about the data trends to keep an eye on in 2021
Advanced analytics bolstering the capabilities of data teams in the cloud is an exciting trend, but it’s just one of several developments we have our eyes on in 2021. To learn more about the data trends we expect to emerge this year, download the ebook, Top Data Integration Trends in 2021.