Waterline Data automates the cataloging of data assets and provides an Amazon.com-like guided shopping approach to data discovery that is intended to take the guesswork out of targeting the right data.
In this report, Forrester Research recommends that application development and delivery (AD&D) professionals working on BI and big data initiatives get the best out of both by designing and integrating them in a flexible data platform.
Information governance and master data management initiatives are complex and require participation from a broad range of enterprise constituents. We focus on five small and innovative vendors that may help information managers reach their information governance and MDM goals.
Today, businesses pour Big Data into data lakes to help them answer the big questions:
Which product to take to market?
How to reduce fraud?
How to retain more customers?
People need to get these answers faster than ever before to reduce “time to answer” from months to minutes. The data is coming in fast and the answers must come just as fast.
The answer is self-service data preparation and analytics tools, but with that comes an expectation that the right data is going to be there. Only by using a data catalog can you find the right data quickly to get the expected insight and business value. Download this white paper to learn more!
Business users want the power of analytics—but analytics can only be as good as the data. The biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation. The increasing volume, variety, and velocity of data is putting pressure on organizations to rethink traditional methods of preparing data for reporting, analysis, and sharing.
Download this white paper to find out how you can improve your data preparation for business analytics.
Business users want the power of analytics—but analytics can only be as good as the data. To perform data discovery and exploration, use analytics to define desired business outcomes, and derive insights to help attain those outcomes, users need good, relevant data. Executives, managers, and other professionals are reaching for self-service technologies so they can be less reliant on IT and move into advanced analytics formerly limited to data scientists and statisticians. However, the biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation.
For many years, traditional businesses have had a systematic set of processes and practices for deploying, operating and disposing of tangible assets and some forms of intangible asset. Through significant growth in our inquiry discussions with clients, and in observing increased attention from industry regulators, Gartner now sees the recognition that information is an asset becoming increasingly pervasive. At the same time, CDOs and other data and analytics leaders must take into account both internally generated datasets and exogenous sources, such as data from partners, open data and content from data brokers and analytics marketplaces, as they come to terms with the ever-increasing quantity and complexity of information assets. This task is clearly impossible if the organization lacks a clear view of what data is available, how to access it, its fitness for purpose in the contexts in which it is needed, and who is responsible for it.
Published By: Veritas
Published Date: May 12, 2016
This inforgraphic highlights that a ‘store everything’ hoarding culture is forming ‘databergs’: where masses of unstructured, irrelevant, unseen or unclassified data is growing daily with no notion of slowing down. They conceal a threat ‘below the waterline’ that adds significant levels of risk and cost to organisations. And this risk is rising.
In our 29-criteria evaluation of machine learning
data catalogs (MLDCs) providers, we identified
the 12 most significant ones — Alation,
Cambridge Semantics, Cloudera, Collibra,
Hortonworks, IBM, Infogix, Informatica, Oracle,
Reltio, Unifi Software, and Waterline Data —
and researched, analyzed, and scored them.
This report shows how each provider measures
up and helps enterprise architecture (EA)
professionals make the right choice.
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