For enterprises, a smart data strategy has transformed from a “nice to have” into a “need to have”—data is the new oil. Companies turn data into a competitive advantage using architectures that gather, secure, access, and analyze data. When evaluating which building blocks—data tools and approaches—to utilize, enterprises should keep in mind several key trends that are driving the future of data infrastructure.
The first of these trends is the rapid shift to the cloud of enterprise data. According to Flexera’s 2020 Annual State of the Cloud Report, 93% of enterprises have a multi-cloud strategy and 87% have a hybrid cloud strategy. Furthermore, COVID has only accelerated the adoption of the cloud, with nearly 60% of enterprises expecting cloud usage to exceed pre-COVID plans.
The reverberations of the transition to the cloud can be felt along the data value chain, from ingestion to analytics. This shift underlies the massive success of data cloud provider Snowflake, now an $80B+ company, following its successful September IPO. A host of companies assist enterprises with backing up (Rubrik), cataloging (Collibra), and transporting (Fivetran) data stored in the cloud. On the analytics front, new tools such as ThoughtSpot Cloud integrate with cloud data warehouses to provide real time insights by querying where data lives.
The rise of the business user is another key trend influencing enterprise data strategies. Historically data insights were accessible only through a small team of specially trained data scientists. Increasingly, enterprises are striving to democratize access to data and enable business users to derive insights. Usable data must, therefore, be available when and where a business need arises. Data observability companies such as Monte Carlo, ensure the quality of incoming data, while transport companies such as Fivetran make data instantaneously accessible in an easy to analyze format. New Business Intelligence (BI) tools offer self-service, search capabilities with user interfaces that do not require SQL training.
Increasingly, enterprises are incorporating AI into their data strategy and data infrastructure stack. Algorithmia helps enterprises deploy, operate, and secure machine learning models using company data. Similarly, Tecton offers a feature store for machine learning models that empowers enterprises to build models and put them into production at scale.
Security and governance are paramount for both traditional and AI-specific data infrastructure. Companies such as Immuta andInCountry provide global data governance options as endpoints become more difficult to protect, while privacy companies such as Privacera and Skyflow protect an enterprise’s sensitive data. As AI/ML become mainstream, concerns have arisen regarding the impact on privacy and ethics. Calypso AI addresses these concerns by ensuring reproducibility and transparency of ML pipelines and models with its AI security and monitoring solution.
The trends outlined above are only a few of many that are shaping the rapidly growing data infrastructure space. How does an enterprise adapt to these trends and maximize the value of its data? Join us in examining the Future of Cloud Based Data Infrastructure at this years’ The Montgomery Summit 2021 presented by March Capital on March 3rd and 4th, where we will examine this question and hear from several of the companies mentioned above that are helping businesses make the most of their data. To register for the 2021 Summit, please click the following link: https://cvent.me/mqWNGX. If you have any questions, please contact firstname.lastname@example.org.