Tag Archives for " data lake "

Enterprise Data Governance with Modern Data Catalog Platforms

Data catalogs, a category of product in the broad field of data governance, are emerging in popularity.

That popularity has been brought on by the twin enterprise mandates of complying with data regulations and herding the growing number of repositories in the corporate data estate.

But data catalogs are a legacy product category too, originally stemming from simple data dictionaries  – essentially table layouts with plain-English descriptions of tables and fields.

Today’s data catalogs have grown in capabilities, importance, and integration with other tools.

In a nutshell, data catalog platforms help organizations inventory their data by documenting data set content, location, and structure; and aligning business and technical metadata.

Control Helps Enterprise

This organization yields control, and having control helps enterprises:

Achieve Compliance

Achieve compliance with data protection regulations, through documentation and inventory.

End users know where to get data and will avoid duplicating it.

Organizations can control access to entire data sets where necessary and can better enforce role-based access to data subsets within them.

The EU’s General Data Protection Regulation (GDPR) is in effect now, with very strict fines for non-compliance.

The GDPR’s companion ePrivacy Regulation (ePR) may come into effect in 2019, and the California Consumer Protection Act (CCPA) has been passed and goes into effect on January 1, 2020.

These regulations demand the structure and controls that data catalogs provide.

Improve Data Lake ROI

Improve data lake ROI by making data within the lake more discoverable and increasing the lake’s usability in general.

A well-organized, searchable data catalog makes it easy to find relevant data, analyze it, derive insights, and make decisions with greater speed and conviction.

These are the very reasons most enterprises built their data lakes in the first place.

Unify Data Landscape

Unify the data landscape by creating a consolidated volume of information covering data (pool) lake, data warehouse, and operational databases.

Implemented correctly, data catalogs integrate these components through a shared abstraction, helping customers derive new value from older warehouse and operational database assets.

Bring Data & Business Closer

Bring data and the business closer together, by mapping business entity definitions onto data sets and columns within them.

A great data catalog provides a business glossary that helps business users find the data they need within the context of their own concepts, taxonomies, and vocabulary.

The summary, then, is that catalogs protect enterprises from regulatory jeopardy and benefit them by delivering more value from existing assets.

Today’s data catalogs enable collaboration between custodians of the data (“data stewards” in contemporary parlance) and business users by mapping out the organization’s data, which makes it more usable for analysis, and thereby benefits the organization.

The vendors discussed in this report all provide baseline functionality (discussed in the Definition section, below) and each has its own emphasis.

Broadly speaking, the products break down into those that are more governance-focused, and those that have a penchant for enabling self-service analysis in the organization by data enhancing data discoverability and usability.

Within those two broad categories are sub-emphases, detailed in the diagram below.

Figure 1: Data Catalogs: Categories and Priorities

Each of the above designations will become clearer through the course of this report.

Source: gigaom.com

Using Your Whole Data Lake: How the Operational Facilitates the Predictive

Many companies in the corporate world have attempted to set up their first data lake.  Maybe they bought a Hadoop distribution, and perhaps they spent significant time, money, and effort connecting their CRM, HR, ERP, and marketing systems to it.

And now that these companies have well-crafted, centralized data repositories, in many cases…they just sit there.

But maybe data lakes fall into disuse because they’re not being looked at for what they are.  Most companies see data lakes as auxiliary data warehouses.

And, sure, you can use any number of query technologies against the data in your lake to gain business insights.

But consider that data lakes can – and should – also serve as the foundation for operational, real-time corporate applications that embed AI and predictive analytics.

These two uses of data lakes — for (a) operational applications as well as for (b) insights and predictive analysis — aren’t mutually exclusive, either. With the right architecture, one can dovetail gracefully into the other.

But what database technologies can query and analyze, build machine learning models, and power microservices and applications directly on the data lake?

Join us for this free 1-hour webinar from GigaOm Research.  The Webinar features GigaOm analyst Andrew Brust, and Splice Machine CEO and Co-Founder, Monte Zweben.

The discussion will explore how to leverage data lakes as the underpinning of application platforms, driving efficient operations, and predictive analytics that supports real-time decisions.

In this 1-hour webinar, you will discover:

• Why data latency is the enemy and data currency is key to digital transformation success
• Why operational database workloads, analytics, and construction of predictive models should not be segregated activities
• How operational databases can support continually trained predictive models

Register now to join GigaOm Research and Splice Machine for this free expert webinar.

Who Should Attend:

• CIOs
• CTOs
• Chief Data Officers
• Digital Transformation Facilitators
• Application Developers
• Business Analysts
• Data Engineers
• Data Scientists

Source: gigaom.com