Alation recently announced the release of its 2021.1 version, introducing new data governance capabilities, enhancements in search and discovery through data domains, and extended connector and query coverage for data sources. Alation’s new federated authentication enables users to query cloud services such as Amazon Web Services, Snowflake, Tableau and more, using a single sign-on. The release also includes a Search application programming interface that allows for the integration of Alation Search with third-party tools. And, with the addition of the Open Connector Framework software development kit in the 2021.1 update, Alation enables organizations to create connectors for data sources not already supported by Alation.
Data is growing exponentially within organizations, making it more difficult than ever to find the right data. At the same time, there are more rules and regulations, such as General Data Protection Regulation and the California Consumer Privacy Act. Not only is data access becoming complicated, but data governance has become a challenge as well. We assert that through 2023, three-quarters of Chief Data Officers' primary concerns will be governing the privacy and security of their organization's data. It’s critical to understand the kind of data that organizations have at present, who is moving it, what it’s being used for and how it needs to be protected. Organizations should also avoid putting too many layers and wrappers around the data because data is useless if it’s too difficult to access and use.
Alation offers its data catalog as a platform for data search and discovery, data governance, data stewardship, analytics and digital transformation. Alation started out as a data catalog software company built originally to support data analysts and the trend toward self-service. With its Behavioral Analysis Engine, inbuilt collaboration capabilities and open interfaces, Alation provides a platform to support a broad range of data intelligence solutions by combining machine learning with human insight for data management.
Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. A modern data catalog includes many features and functions that all depend on the core capability of cataloging data — collecting the metadata that identifies and describes the inventory of shareable data. Plus, using artificial intelligence and ML for metadata collection, semantic inference and tagging is important to obtain maximum value from automation and minimize manual effort. Data catalogs also offer compliance with internal policies like security and privacy, and external regulations like GDPR and CCPA. AI/ML capabilities can detect “sensitive” data like that governed by the Health Insurance Portability and Accountability Act or personally identifiable information fields, while usage tracking can determine potential access or illegal usage patterns and create an audit trail for compliance.
Alation’s new Open Connect Framework software development kit enables third-parties, including customers and partners, to build connectors to niche relational database management systems and business intelligence data sources. Alation at present has over 90 data sources including SAP BusinessObjects, Dataiku, Tableau Online and Starburst, among others. Through containerization, upgrades to connectors can be managed without disruption to the data catalog. Business personnel can query new types of data sources —such as NoSQL and application sources — directly through Alation’s intelligent SQL editor, decreasing the time it takes to discover and generate insights from data. Alation also enables organizations to implement DataOps for AI/ML projects by offering native version control and change management capabilities to reduce data silos and gain a single view of all enterprise data assets.
Data catalogs enable line-of-business personnel to navigate multiple analytic components, while providing necessary information about each analytic offering to ensure they select the appropriate data asset(s) for their immediate needs. It assists BI developers by identifying what data is available and accessible, what reports have been created, who is affected by changes in the upstream processing of the data, and which assets are no longer being used.
Data analysts and data scientists spend too much time finding and understanding data, often recreating datasets that already exist. In fact, our research shows the most common challenge in applying ML is accessing and preparing data. Workers frequently deal with inadequate datasets, resulting in inadequate and incorrect analysis. With a data catalog, the line of business can search and find data more quickly, see all available datasets, evaluate and make informed choices for which data to use, and perform data preparation and analysis efficiently.
I recommend that organizations looking to make data access easier and improve data collaboration include Alation in their vendor evaluation list.