AtScale, the company to provide enterprises with a fast and secure self-service BI platform for Big Data, announced a significant expansion of its services, from BI on Hadoop to BI on Big Data. With this announcement, the company introduces a Modern BI Platform that enables businesses to work seamlessly across all of Big Data, on premise and in the Cloud. In addition to Hadoop, the AtScale platform now supports Teradata data warehouses and Google Dataproc and BigQuery. This expands on the company’s existing support for Microsoft Azure and HDInsight.
AtScale redefines the modern Business Intelligence Platform to enable lightning fast, interactive and secure analytics on top of Big Data, without data movement and for any data consumer or BI tool.
A modern analytic platform standardizes on what’s important, an interactive business view of big data that any tool or application can access, balancing the need for unfettered exploration with standards to ensure data consistency. says Wayne Eckerson, a thought leader in the business intelligence and analytics field. “In this regard, AtScale is ahead of the pack.”
The company, which counts some of the largest enterprises in the world as customers, has grown revenue by more than 10X since it launched 2 years ago. Corporations like American Express, Macy’s, Comcast, GlaxoSmithKline, Home Depot, Groupon, Bloomberg and many others have participated in the evolution of AtScale’s vision. Cloudera became an AtScale customer very early on and Hortonworks licensed AtScale as part of a historical worldwide resell deal in mid-2016.
The Modern Business Intelligence Platform
We’ve had exposure to some of the most sophisticated use cases for enterprise business intelligence,” says Matt Baird, co-founder and CTO at AtScale. “And every single customer has asked us to extend our capabilities across the rest of their data portfolio. This was part of our vision all along: I just didn’t expect customers would ask for it so soon!”
AtScale’s founding team laid out this vision over 6 years ago: create a modern Business Intelligence platform that can perform queries at interactive speed and scale for any type of data, wherever that data lies: Hadoop, non-Hadoop, on Premises, and in the Cloud.
As customers embraced AtScale’s approach, the industry realized that enterprises were not buying BI the same way they had 20 years ago,” says Jerry Yang, AME Cloud Ventures Founding Partner and Co-founder of Yahoo! “Enterprises now expect their BI platform to work with any BI tool, whether it talks SQL or MDX, whether it’s packaged or open source. AtScale is the only solution to address this need.”
The same goes of data access, integration and movement. Traditional approaches require that IT departments move disparate data into one centralized data warehouse or data marts, a legacy approach that has shown its limits by costing time, agility and money to organizations. AtScale is the only industry solution that can apply its semantic model across Big Data, without data movement, whether it’s in Hadoop or not, whether it’s on-premises or in the Cloud. Unlike legacy approaches, AtScale brings business users to the data rather than moving data into proprietary, purpose-built silos.
A Framework for “Big Business Intelligence”
The average BI platform company is 22 years old,” says Dave Mariani, CEO and co-founder at AtScale. “We can’t expect them to work well on today’s data stack. We certainly shouldn’t count on them alone for the data platforms of tomorrow: trying to scale BI in ways that are reaching the limits of a quarter century old framework is the road to disappointment.”
AtScale indeed proposes a new way to frame people’s needs for insights on Big Data:
- One Data Model Across all BI Tools: When considering a modern BI platform, enterprises should take an inventory of the various visualization tools they own. Most companies have 10s, sometimes 100s. They then need to assess the viability of an IT strategy that would force users to abandon their preferred tools (which may include Excel, Tableau or others) for the sake of supporting new data platforms like Hadoop or Google BigQuery. The most successful enterprises enable employees to draw insights from within the tools they already own, use and love.
- Standardize Where It Matters: When considering standardization, enterprises have historically worked on large enterprise data warehouse (EDW) projects. Most EDW projects take too long or fail, leaving the organization with a hodgepodge of data assets, each governed by siloed definitions and business models. This has created chaos and affected enterprises’ ability to work off consistent and well-understood business metrics. The most successful enterprises do not move data around. Rather, they use a Universal Semantic Layer™ like AtScale’s to define business logic centrally, regardless what BI tools people use, regardless of whether the data is in Hadoop, notin Hadoop, on-premises or in the Cloud.
- Leverage Open Source: When it comes to insights for employees, speed matters: any query returning in more than 60 seconds is not interactive. Customers that are struggling with speed often do so because they’ve been on proprietary engines or antiquated approaches such as data marts, extracts or exports. Over the last 6 months, most SQL-on-Big-Data engines have more than doubled their speed. In other words, modern BI platforms that leverage open-source have experienced performance benefits faster than any proprietary effort.
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