Getting ready for AI, data lakes or a big swamp

Genpact

If data is indeed the gold that enterprises mine on their way to an AI-first world, how do we extract, refine and make it available in its most efficient manner? That's the overarching question as Genpact's CDO, Sanjay Srivastava, moderates an all-star panel of experts that includes: VP Enterprise Services Platforms at PayPal Tushar ShahPartner and, CTO at 8VC Bhaskar Ghosh, Microsoft Data Science Leader Barbara Stortz, and Genpact Analytics Services Leader Amaresh Tripathy.
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Spotlight

Data warehouses have been the foundation for business analytics for many years, and have grown to support increasing data volumes as well as analytics and ETL workloads. Yet over time, some data becomes older and is used infrequently or not at all. And ETL workloads implemented as transformations inside the data warehouse can grow to occupy significant CPU cycles, impacting resources that support critical analytics processes.


OTHER ON-DEMAND WEBINARS

The Big Data Organization: Get the Right People on Your Big Data Bus

Big data has ushered in a host of new development and usage models. Open source projects have become software products, end users have become knowledge workers, statisticians have become data scientists and new chief officers are on the rise.
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Improving Transactional Applications with Analytics

MariaDB

Today, most web and mobile applications are limited to “lightweight” analytics because general-purpose databases can be optimized for transactional or analytical workloads, but not both – and since transactional processing is critical, applications have to compromise on analytics. However, what if an e-commerce application could let customers know which products are soon to be sold out based on clickstream data, shopping carts, current inventory and recent purchases as well as historical buying patterns and emerging shopping trends? In this webinar, attendees will learn how to leverage MariaDB ColumnStore to provide transactional applications with real-time analytics on historical data.
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Mastering the Upsell

Gainsight

One of the biggest ways CSMs can add value to their company is by identifying clients who are ready for an upsell. Timing is everything. Too early and you’ll only exasperate your customer. Too late and the opportunity will pass you by.
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Five Tips for Moving your RDBMS project to the Big Data world using SQL on Hadoop & SPARK

TechGig

Many groups wishing to migrate their RDBMS workloads to Big Data feel they can't justify the updgrade of technology because their data is doesn't fit the NoSQL model or it itsn't large enough to quality as Big Data or it is not unstructured. This session will show you why it makes sense to migrate your RDBMS project to SQL on Hadoop & Spark and five tips on how to do it properly to get the most benefit from a business and technical standpoint.
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Spotlight

Data warehouses have been the foundation for business analytics for many years, and have grown to support increasing data volumes as well as analytics and ETL workloads. Yet over time, some data becomes older and is used infrequently or not at all. And ETL workloads implemented as transformations inside the data warehouse can grow to occupy significant CPU cycles, impacting resources that support critical analytics processes.

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