How to Get Your Ingested Data Production-Ready in Just 8 Weeks

Posted by Kelly Schupp, VP, Data-Driven Marketing on Feb 23, 2017 3:21:01 PM

Whether you’re planning for a data lake implementation or have a proof-of-concept (POC) in place, one thing is clear: You must hydrate the data lake before it can be ready for production. Depending on the complexity and volume, data ingestion and data preparation can take at least six months.

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Topics: Big Data Ecosystem, Bedrock, Data Lake, Data Management, Data Governance, Metadata Management

Managed Data Lakes Enable the Promise of the New Health

Posted by John Poonnen on Feb 22, 2017 10:24:55 AM

Physicians and care teams must now focus on the optimal delivery of care, through broad, proactive population health management initiatives and effective personalized medicine. This transformation requires an real-time, integrated, holistic view of data from many diverse sources to provide a comprehensive 360 degree view of the patient along with the context of the population being treated.  Creating-managing-exposing information captured in managed data lakes can help healthcare organizations understand their patients and their subpopulations, thus making personalized, proactive evidence based medicine a reality.

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Topics: Industries & Use Cases, Bedrock, Data Lake, Data Governance

What Is Metadata and Why Is It Critical in Today’s Data Environment?

Posted by Scott Gidley on Feb 15, 2017 3:43:06 PM

Excerpt from ebook, Understanding Metadata: Create the Foundation for a Scalable Data Architecture, by Federico Castanedo and Scott Gidley.

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Topics: Big Data Ecosystem, Data Lake, Data Management, Metadata Management

Zaloni Zip: Solving the Challenges of Hybrid Data Lake Architecture

Posted by Parth Patel on Feb 14, 2017 3:47:07 PM

In this Zaloni Zip, we will discuss the challenges of a Hybrid Data-Lake architecture and how Zaloni’s centralized data-lake management platform tackles those challenges head-on. 

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Topics: Big Data Ecosystem, Bedrock, Zaloni Zip, Data Lake, Data Management, Data Governance, Metadata Management

New Releases of Bedrock and Mica Expand Data Lake Beyond Hadoop

Posted by Kelly Schupp, VP, Data-Driven Marketing on Feb 9, 2017 9:33:09 AM

With our latest Bedrock and Mica updates, we’re pushing the boundaries of what has up until now typically defined a data lake: Hadoop. Why are we moving in this direction? Because it makes sense for our clients, who need a solution to centralize management of data from siloed data systems, legacy databases and hybrid architectures. Our solutions support the concept of a data lake beyond Hadoop to encompass a more holistic, enterprise-wide approach. By constructing a “logical” data lake architecture versus a physical one, we can give companies transparency into all of their data regardless of its location, enable application of enterprise-wide governance capabilities, and allow for expanded, controlled access for self-serve business users across the organization.

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Topics: Hadoop, Big Data Ecosystem, Bedrock, Zaloni News, Data Lake, Data Management, Mica, Data Governance, Metadata Management

Up Your Game: How to Rock Data Quality Checks in the Data Lake

Posted by Adam Diaz on Feb 7, 2017 2:52:06 PM

Common sense tells us one can’t use data unless its quality is understood. Data quality checks are critical for the data lake – but it’s not unusual for companies to initially gloss over this process in the rush to move data into less-costly and scalable Hadoop storage especially during initial adoption. After all isn't landing data into Hadoop with little definition of schema and data quality what Hadoop is all about? After landing data in a raw zone in Hadoop the reality quickly sets in that in order for data to useful both structure and data quality must be applied. Defining data quality rules becomes particularly important depending on what sort of data you’re bringing into the data lake; for example, large volumes of data from machines and sensors.  Data validation is essential because it is coming from an external environment and it probably hasn’t gone through any quality checks.

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Topics: Hadoop, Big Data Ecosystem, Bedrock, Data Lake Solutions, Data Warehouse, Data Lake, Metadata Management

Analysis in 10 Minutes (or Less!) with AWS QuickSight

Posted by Rajesh Nadipalli on Feb 2, 2017 4:09:57 PM

AWS QuickSight is the next generation Business Intelligence (BI) application that can help build interactive visualizations on top of various data sources that are hosted on Amazon cloud infrastructure. In this post, I will show you how easy it is to build your first analysis in under 10 minutes all in the AWS cloud infrastructure.

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Topics: Big Data Ecosystem, Data Lake, Data Management

Integrating Big Data Platforms with Bedrock: REST API

Posted by Adam Diaz on Feb 1, 2017 1:12:21 PM

In conversations about the Bedrock Data Lake Management Platform, the most common question we hear is “Can Bedrock integrate with product X?” which is almost immediately followed by “Can I use Bedrock without the UI?”. The answer to both is “Yes.” And it’s all made possible by the robust REST API that is built into Bedrock.

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Topics: Big Data Ecosystem, Bedrock, Data Lake, Data Management

How Data Lakes Work

Posted by Ben Sharma on Jan 26, 2017 8:06:19 AM

Excerpt from ebook, Architecting Data Lakes: Data Management Architectures for Advanced Business Use Cases, by Ben Sharma and Alice LaPlante.

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Topics: Hadoop, Ben Sharma, Big Data Ecosystem, Data Warehouse, Data Lake, Data Management

AWS QuickSight: Interactive Business Intelligence for Faster Insights

Posted by Rajesh Nadipalli on Jan 25, 2017 3:15:31 PM

This blog is the first in a series on AWS QuickSight. AWS QuickSight is the next generation Business Intelligence (BI) application that can help build interactive visualizations on top of various data sources hosted on Amazon cloud infrastructure. QuickSight delivers fast and responsive insights on Big Data, enables organizations to quickly democratize data visualizations and scales to hundreds of users at a fraction of the cost when compared to traditional BI tools.

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Topics: Big Data Ecosystem, Data Lake, Data Management