Tuning Hive on Tez queries can never be done in a one-size-fits-all approach. The performance on queries depends on the size of the data, file types, query design, and query patterns. During performance testing, evaluate and validate configuration parameters and any SQL modifications.
Customers who work with data warehouses, running BI on large datasets used to have to pick low latency but trading off freshness of data. With BigQuery BI Engine, they can accelerate their dashboards and reports that connect to BigQuery without having to sacrifice freshness of the data. Using the latest insights helps them make better decisions for the business.
We like to keep things light at Unravel. In a recent event, we hosted a group of industry experts for a night of laughs and drinks as we discussed cloud migration and heard from our friends at Don’t Tell Comedy. Unravel VP of Solutions Engineering Chris Santiago and AWS Sr. Worldwide Business Development Manager for Analytics Kiran Guduguntla moderated a discussion with data professionals from Black Knight, TJX Companies, AT&T Systems, Georgia Pacific, and IBM, among others.
The term DataOps (like its older cousin, DevOps) means different things to different people. But one thing that everyone agrees on is its objective: accelerate the delivery of data-driven insights to the business quickly and reliably.
Business intelligence empowers businesses to get the most out of their data by providing tools to analyze information, streamline operations, track performance, and inform decision-making. In the Microsoft Dynamics ecosystem, Power BI generates easy-to-read visualizations that help stakeholders perform key analysis. But finance professionals can encounter roadblocks when seeking deeper analysis than their technical knowledge of Power BI permits.
Fraud, waste, and abuse (FWA) in government is a constant, multi-billion dollar issue that challenges agency leaders at all levels and across all sectors, from healthcare to education to taxation to Social Security. The scope and scale of public spending—federal outlays alone were approximately $6.6 trillion in fiscal year 2020 according to the Congressional Budget Office—make FWA an inherently difficult problem to solve.
Marketing based on the next best action requires effective data handling for success. For Canadian insurer, Beneva, however, silos were standing squarely in the way. With over three million customers and CA$13 billion in assets, Beneva is one of Canada’s largest financial institutions. They had over 75 years of product and customer data, but that data was isolated in various systems, databases, and customer portals.
