Starburst’s business is built to solve an analytics challenge most companies face: How can they extract value from all their data quickly? In a world where distributed data is here to stay, there’s no longer a one-size-fits all solution. We believe the ‘Single Source of Truth’ vision, made famous by the Enterprise Data Warehouse model, is not achievable. It’s led companies on a never-ending data movement quest, creating complex ETL + ELT pipelines (which are in constant break-fix mode). A lot of inefficiencies have been built into data management practices because of this failed paradigm – the idea that you can and should move all of your data into one place for analytics.
However, we don’t believe the Data Warehouse is dead, nor data movement – but we do see an overreliance on this approach. This creates delays in critical decision-making as data analysts and scientists are perpetually waiting to get access to new and newly critical data.
The COVID-19 pandemic has showcased how unprepared most companies were to quickly harness new data and adapt to changing behaviors. When the world went digital overnight, this created a complete inverse of physical to digital behaviors. As an example, retail was formerly 90% instore, 10% online transactions – and boom – 90% online, 10% instore. Those who were prepared for this were ok, retailers (including grocers) who were late to the digital game have struggled.
While we all know this has been one long strange journey, it’s just another example of companies needing a better way to efficiently make data-driven decisions. Whether that be how to stand up a better eCommerce experience that’ll engage & convert buyers, or how to bring new demand signals into your supply chain planning.
Simply put: Companies can’t afford to wait for data access. In a recent survey we conducted with Red Hat “The State of Data and What’s Next” we found 56% of companies found data access was more critical post-pandemic, but 37% of companies were not confident in their ability to access timely relevant data for critical decision making.
Gartner introduced a new category of ‘Analytics Query Accelerators’ through their report, Market Guide for Analytics Query Accelerators. The report focuses on helping data and analytics leaders get more value out of their data lake initiatives, in particular, where the majority of new data resides. According to the research report authored by analysts Adam Ronthal, Merv Adrian, and Henry Cook, “Analytics query accelerators are unlikely to replace the data warehouse, but they can make the data lake significantly more valuable for less skilled consumers.”
Analytics query accelerators provide SQL or SQL-like query support on a broad range of data sources. Gartner recommends data and analytics leaders test query accelerators against complex workloads to evaluate performance improvements, test integration with surrounding cloud data management, evaluate security, and governance capabilities to ensure they meet enterprise standards.
We’ve done a lot of work to provide large companies with a single point of access to all their data, no matter where or in what format this data resides. We see Starburst Enterprise as the clear leader in providing performance, stability, and secure connectivity across many data sources. Watch this great video of our customer EMIS as they describe how they’re able to leverage more data sources, more quickly, for critical insights that improve patient outcomes:
We recognize that we’re operating in a complex and crowded ecosystem. Between all the AI platforms, data warehouses, cloud data lakes, lakehouses, Business Intelligence (BI) and Data Analytics tools and more, we know it’s hard for companies to determine which solution provider is actually going to give you what you need. The Gartner report will help you contextualize things and get a better understanding of where Starburst Enterprise and other vendors fit.
