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

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

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 Big Data is Powering Next Generation Loyalty Programs and Increasing Customer Satisfaction

Posted by Annie Bishop on Jan 5, 2017 1:19:53 PM

Traditionally loyalty programs retain customers by offering rewards and discounts on future purchases. As we’ve transitioned to a world where we have both brick and mortar and ecommerce retail environments and have seen advancements in retail technologies, companies are now able to capture more data about their customers than ever before.

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Topics: Big Data Ecosystem, Bedrock, Data Lake 360, Data Management

Validating Data in the Data Lake: Best Practices

Posted by Tony Fisher, SVP of Strategy and Business Development on Dec 15, 2016 1:27:33 PM

Can you trust the data in your data lake? Many companies are guilty of dumping data into the data lake without a strategy for keeping track of what’s being ingested. This leads to a murky, swampy repository. If you don’t have transparency into your lake so that you can feel confident using the data, what’s the point of deploying a data lake in the first place?

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Topics: Hadoop, Big Data Ecosystem, Bedrock, Data Lake, Data Governance

Building a Machine Learning Engine from Big Data

Posted by Aashish Majethia on Dec 9, 2016 8:11:10 AM

Machine learning (ML) is still growing as a field in big data and has of late made some significant advances. In fact, practical applications have become quite commonplace and most of us have benefited from it already. Email providers use it to determine whether an email is spam or legitimate. Credit card companies use it to flag potentially fraudulent charges. Hospitals are using it to improve outcomes for patients. If you’re a Netflix customer, you may have even been suggested a movie using machine learning :-)  It’s obviously a hot topic and is making it’s way across newer industries as capabilities grow. A simple ‘machine learning’ search on Amazon returns over 13,000 books.

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Topics: Hadoop, Big Data Ecosystem, Data Science, Bedrock, Machine Learning

Data Lake Archiving: Hadoop or the Cloud?

Posted by Ben Sharma on Dec 8, 2016 11:43:30 AM

The storage layer of the data lake is evolving. A few years ago, when we talked about the data lake, it was generally understood that Hadoop was the underlying platform for everything related to the data lake. Today, thanks to the cloud, that is no longer necessarily the case. Why? Deploying a data lake in the cloud enables you to decouple storage and compute functions and use the storage platform that is best suited and most cost-effective for your needs – which may not be Hadoop.

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Topics: Hadoop, Ben Sharma, Big Data Ecosystem, Bedrock, Next-Gen Data Lake, Data Lake