Expanding Biobanking Size and Scope to Advance Big Data Discovery

LabRoots

Currently, the Cleveland Clinic Biorepository is an assembly of several biobanks together with the Lerner Research Institute. Excel spreadsheets track almost everything – and there are no universal LIS, SOPs, universal, centralized freezer monitoring, or means to electronically track patient tissue. The Cleveland Clinic is embarking on an enterprise-wide initiative to accelerate its biobanking capacity, leveraging its clinical volume and disease expertise. As part of this initiative, the Cleveland Clinic is partnering with Brooks Life Sciences to build a state of the art, 21,000 square-foot structure biobanking facility, set to open in the summer of 2019.
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Spotlight

In business publications and IT trade journals, the buzz about “big data” challenges is nearly deafening. Rapidly growing volumes of data – from transactional systems like enterprise resource planning (ERP) software and non-transactional sources such as web logs, customer call center records, and video images – are everywhere. A tsunami of data, some experts call it. Most companies know how to collect, store, and analyze their operational data. But these new multi-structured data types are often too variable and dynamic to be costeffectively captured in a traditional data schema using only a standard query language (SQL) for analytics.

OTHER ON-DEMAND WEBINARS

Sprint or Marathon? Going the distance with data center maintenance

Navigating the course of data center management comes with a multitude of obstacles. Most IT professionals must balance maximizing uptime, improving security, optimizing operations and meeting budget realities. In the case of data center maintenance, what is the best route to take after initial warranty support expires? Uptime a
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How to Scale New Products with a Data Lake on AWS and Qubole

awscloud.com

Big data technologies can be both complex and involve time consuming manual processes. Organizations that intelligently automate big data operations lower their costs, make their teams more productive, scale more efficiently, and reduce the risk of failure.
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What’s Ahead in Data Management in 2019?

tdwi.org

This webinar is a must attend for technical users and business managers who are facing these changes. The expert panel on this webinar will help attendees understand what’s ahead in 2019 and beyond for data management. Attendees can then apply that information to prioritize the data management changes they must address and how they will prepare via hiring, training, budgeting, making a business case, and adopting the right data platforms and tools.
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Gain Context, Insight and Value from Big Content

OpenText

The Internet of Things, social media and enterprise content all have one thing in common: they generate vast quantities of data — ever-faster. So much so that picking out relevant information and assembling it into meaningful patterns is a tall order. These new data sources also present another challenge. They generate unstructured data - such as text and emojis - that don’t fit neatly into traditional database structures. This data can however hold valuable insights on important and hard-to-quantify concepts such as social sentiment.
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Spotlight

In business publications and IT trade journals, the buzz about “big data” challenges is nearly deafening. Rapidly growing volumes of data – from transactional systems like enterprise resource planning (ERP) software and non-transactional sources such as web logs, customer call center records, and video images – are everywhere. A tsunami of data, some experts call it. Most companies know how to collect, store, and analyze their operational data. But these new multi-structured data types are often too variable and dynamic to be costeffectively captured in a traditional data schema using only a standard query language (SQL) for analytics.

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