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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Spotlight

Text Analytics is a key feature of IBM's Big Data platform. In part one of this two part series, Vijay Bommireddipalli, a Big Data Solution Architect, gives us an introduction to Text Analytics and IBM's capabilities in this area.

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Oracle Autonomous Database - Keep Data More Secured, Eliminate Costly Data Breaches

Oracle

Data, the life blood of today's economy, is an attractive target for cyber attackers. Learn how a self-securing database provides security and peace of mind without relying on manual, error-prone processes allowing you to focus on innovation and not damage control.
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Unleash the Power of Your Finance Data

In today’s corporate finance departments, the pressure to do more with less is greater than ever. The most successful finance teams partner with other lines of business to drive growth through data-driven insights, using advanced analytics and predictive models. But translating insights into real-time actions requires real-time analytics that can’t be achieved with traditional business intelligence solutions and dashboards. To unleash the full power of your finance data, you need a new approach.
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Key Elements of a Successful Data Governance Program

At its core, Data Governance (DG) is all about managing data with guidance. This immediately provokes the question: Would you tolerate any of your assets to be managed without guidance? (In all likelihood, your organization has been managing data without adequate guidance and this accounts for its current, less-than-optimal state.) This program provides a practical guide to implementing DG or recharging your existing program. It provides an understanding of what Data Governance functions are required and how they fit with other Data Management disciplines. Understanding these aspects is a prerequisite to eliminate the ambiguity that often surrounds initial discussions and implement effective Data Governance/Stewardship programs that manage data in support of organizational strategy. Delegates will understand why Data Governance can be tricky for organizations due to data’s confounding characteristics.
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How to Use Data Prep to Accelerate Cloud Data Lake Adoption

tdwi

What began as a trickle is now the mainstream: Organizations are moving to the cloud for data management. No longer is the cloud just a cheaper place to park data; it is key to supporting business-critical innovation in advanced analytics, data science, and AI as well as for end-user business intelligence, data exploration, and data visualization. Data lakes and data warehouses running on market-leading platforms such as AWS are growing fast, just as they are on the platforms of competing providers. However, as cloud-based workloads grow in number and size, organizations are facing difficult data preparation challenges. The flow of data raw, diverse, and frequently unstructured can quickly turn cloud data lakes into impenetrable swamps. Without good data preparation technologies and practices, users of all types are frustrated; their productivity and satisfaction suffer because it’s too hard to get accurate data that’s appropriately transformed and structured for their purposes.
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Spotlight

Text Analytics is a key feature of IBM's Big Data platform. In part one of this two part series, Vijay Bommireddipalli, a Big Data Solution Architect, gives us an introduction to Text Analytics and IBM's capabilities in this area.

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