December 31, 2019Our Top 5 Blog Posts of 2019
The movement of analytical workloads to cloud data warehouses such as Google BigQuery, Snowflake, Amazon Redshift, and Microsoft Azure is a trend that will only continue to grow. The performance and cost benefits of these cloud providers compared to legacy data warehouses like Teradata or distributed systems like Hadoop are too great for decision makers at the world’s largest enterprises to ignore. However, cloud transformation is a challenging multi-year process for even the most nimble enterprises, and there are doubts about whether all data will live in the cloud in the foreseeable future. Hybrid cloud environments, meaning a combination of cloud and on-premise data warehouses, are the likely corporate standard for data management over the next decade.
While the hybrid cloud represents an improvement from on-premise data environments, it can still be slow, cumbersome, and expensive to maintain both traditional on-premises data warehouses and multiple online data sources. Migrating to new data repositories can be disruptive for business users who have time-critical analyses to conduct. Curation and management of siloed data is a drain on resources, and the proliferation of BI tools, with each department and business unit nurturing local favorites with different interface requirements, make getting consistent and accurate answers to questions across groups challenging.
What is A Virtual Data Warehouse?
What businesses need is a solution that intelligently virtualizes all their siloed data into a single, unified data view from which a variety of BI tools can get fast, consistent answers. AtScale’s A3 platform solves the three critical challenges facing companies with large data warehousing needs looking to move to the cloud:
- Provide a universal interface for BI tools so that departments and business units can get consistent answers to the same question, even when using different BI tools.
- Virtualize all data sources so they can be presented as a single, unified data view to maximize their value to BI tools.
- Accelerate queries, reduce costs, and protect sensitive data from unauthorized access
AtScale’s Adaptive Analytics Fabric Improves BI Performance on any Tool
With the proliferation of excellent BI tools, each department and business unit may have its own favorite. According to Forbes, 60% to 70% of business functions utilize two or more BI tools. Rather than forcing them onto a single BI solution, which would require retraining and almost certainly suffer from user adoption issues, companies need a solution that can enable a variety of BI tools to connect to their data.
AtScale enables business users to conduct interactive and multidimensional analysis using the BI tools of their choice, whether it is Excel, PowerBI, or Tableau. Different BI tools have varying dialects of query languages, making it complicated for IT to support. Disparate query dialects or languages also makes it difficult to ensure business users are receiving the same answers to the same queries across tools.
AtScale solves this query consistency challenge by providing a “Universal Semantic Layer” that translates the BI queries into uniform and standardized queries against A3. AtScale’s Universal Semantic Layer supports a great variety of BI tools regardless of the access protocol required, whether it is MDX, SQL, JDBC, ODBC or Rest API, and supports the most complex queries and mature data analyses.
Present Data from Disparate Systems to BI Users in a Single View
IT professionals know the pain of trying to bring together siloed and far flung data sources. AtScale data virtualization takes data stored in different locations, often with different data architectures and formats, and presents them as a single, unified data experience for business users. Virtualization allows enterprises to have the benefits of a virtual data warehouse, while the data itself may still reside in disparate cloud and on-premise data warehouses. Business users query the data without concern for where that data lives or how it might be distributed across their company’s various data repositories.
While cloud data warehouses’ pay-as-you-go pricing model is more economically appealing than the legacy model of paying for all data that is stored, migrating to the cloud does not guarantee significant cost savings. Running queries that scan billions of rows of raw data can incur steep charges that negate the cost savings of the cloud. Enterprises need a smart approach to embracing the cloud, and AtScale Intelligent Aggregates can significantly reduce data warehousing and query costs.
When queries are run against the fabric, they rarely require the totality of the data available. AtScale’s machine learning capabilities automatically identify the data patterns of queries and generate aggregate data tables wherever the data resides, eliminating the need to copy or move records across networks. Queries are then applied to these smaller databases instead of the whole body of enterprise data. Queries no longer need to scan huge volumes of irrelevant records, accelerating query response time and dramatically reducing query costs.
A Virtual Data WarehouseMeets Enterprise Security Requirements
A smart approach to embracing the cloud also means enterprises must attend to data governance and security. AtScale’s Adaptive Analytics Fabric inherits existing security programs while enabling the ability to create additional security measures at the user and cell level. AtScale supports a host of security capabilities such as end-to-end Transport Layer Security (TLS) and the LDAPS secure protocol. AtScale complies with the JWT, CORS, and REST standards for API security, and since Intelligent Aggregates minimize ETL of data, sensitive data is not exposed.
Access controls are managed by AtScale’s patented True Delegation technology. True Delegation satisfies the most stringent data governance and access auditing policies by preserving user-level access controls when querying A3, even when the user is on a shared account, in a process called “delegated authorization.” Every query sent to the virtual data warehouse is associated with the user who generated the query. That user’s access permissions are applied to every row and column of the data being queried, ensuring no data is returned that the user is not authorized to see.
A3 is a Game Changer for Enterprise Data Strategy
An adaptive analytics fabric is now front and center as the technology enterprises will employ to leverage their data assets to maximize agile competitive insights. By eliminating the barriers that prevent business users from using whatever tools they need to address the totality of available data, enterprises will be able to realize the full potential of their business analytics. At the same time, it will also greatly accelerate the pace at which businesses are able to gather insights on key business questions, providing a competitive advantage on slower-moving competitors. AtScale’s Universal Semantic Layer, Autonomous Data Engineering, acceleration structures, and data virtualization capabilities will transform the public and hybrid cloud.