As the BI market continues to mature, Tableau and Microsoft retain their positions as the dominant players in Gartner's 2019 magic quadrant on BI and Analytics. ThoughtSpot and Looker are the two emerging vendors to watch.
As part of its new partnership with Snowflake, AtScale has implemented features that augment Snowflake's use of different-sized warehouses to optimize cost and compute.
Ebates, a leading cashback and rewards website, initially used AtScale to improve analytics performance on Hadoop. AtScale enabled Ebates to seamlessly migrate to Snowflake while continuing to optimize performance on their new cloud data platform.
Enterprises need a Virtual Data Warehouse to provide a single view of their data regardless of where it is stored, accelerate time to insight, and keep data secure.
AtScale empowers enterprises to benefit from Google BigQuery while keeping analysts on Microsoft Excel.
Learn how AtScale enables enterprises to optimize cloud costs and increase query performance on any cloud environment.
Enterprises are trusting cloud data warehouses with greater frequency. Amazon Redshift, Google, and Snowflake are three of the main players in the CDW space.
OLAP emerged in the 1990s with the releases of tools like Essbase and Microsft SQL Server Analysis Services. However, OLAP has been plagued by inefficiency as data volumes have exploded. AtScale's Virtual Data Warehouse empowers enterprises to realize strong BI performance with OLAP.
Hadoop was created with the goal of lowering the cost of analyzing data, but implementations often resulted in similar BI performance challenges. AtScale's use of in-memory aggregates alleviates many of the inefficiencies of BI on Hadoop.
Data architects often have to go to great lengths to model complex business logic in a scalable fashion. AtScale enables this modeling to take place away from BI consumers, allowing more efficient analysis of complex business information.
Most enterprises have data architects that create a data model for how their organization's business intelligence users consume data. AtScale enables these architects to model advanced business logic that doesn't fit into a traditional schema in a manner that can be easily interpreted by BI users.
Financial Services organizations run frequent time specific calculations to measure the health of their businesses. New data platforms have made running these calculations increasingly arduous. AtScale's Intelligent Data Fabric enables business analysts to execute these calculations efficiently.
The ability of a Data Lake to store vast amounts of information carries enormous potential to an enterprise. However, many organizations that employ Data Lakes struggle with BI performance against that data, resulting in individual users creating extracts that detract from the Data Lake's value.
IBM's record breaking purchase of Red Hat is a clear indicator of the opportunity in front of cloud technology providers. Enterprises that migrate data to the cloud in the near term will be able to take the greatest advantage of the cost and performance benefits of doing so.
An intelligent data fabric can enhance companies' tableau performance on an enterprise data warehouse by solving 3 challenges that occur frequently in large tableau implementations.
Snowflake's cloud-based data warehouse enables companies to improve performance while minimizing cost when moving over from traditional data stores. AtScale's intelligent data fabric further augments the business benefits Snowflake provides.
Chief Data Officers play an increasingly important role at large organizations. While most global enterprises have hired a Chief Data Officer or plan to hire one soon, there is a lack of consensus on a CDO's mandate. It is likely that CDOs will drive cloud data transformation projects.
Businesses are using Google BigQuery, Amazon Redshift, and Microsoft Azure to host vast quantities of data. Much of this data remains unused due to slow time to insight. AtScale alleviates the causes of slow time to insight, which enables businesses to derive more value from their data.
AtScale's machine learning allows enterprises to efficiently use business intelligence tools with Amazon's cloud storage solutions. AtScale provides an opportunity for enterprises to save on AWS costs by enabling them to keep more data in S3 without compromising performance.
Cloud environments such as Google BigQuery are the optimal solution for big data workloads due to their ability to easily deliver elastic computing and storage at relatively low cost. AtScale employs aggregation to help enterprises using BigQuery further reduce their storage and processing costs.