Modern Data Analytics in the Cloud: Achieving an End-to-End Strategy

TDWI

Businesses today need fast, scalable, and agile data and analytics, and cloud-based solutions are proving critical to satisfying these requirements. They enable organizations to rapidly and easily spin up systems and services for collecting, managing, and analyzing data. More important, cloud-based solutions deliver value from “data gravity”the surging volumes of new data created in the cloud by social media, the IoT, multichannel customer behavior, and other activity.
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Spotlight

Data analytics are used to test controls and validate that business risks are managed. This would generally occur at a point-in-time when an assurance activity is scheduled. Rather than test a number of transactions, the entire population of transactions can be reviewed for greater coverage. Data analytics includes automated tools such as generalised audit software, test data generators, computerised audit programs, specialised audit utilities and computer-assisted audit techniques (CAATs).

OTHER ON-DEMAND WEBINARS

Building Next-Gen Data Pipelines with Databricks Delta

Databricks

Building performant ETL pipelines to address analytics requirements is hard as data volumes and variety grow at an explosive pace. With existing technologies, data engineers are challenged to deliver data pipelines to support the real-time insight business owners demand from their analytics. Databricks Delta is the next generation of evolution in big data processing from Databricks, the company founded by the original creators of Apache Spark.
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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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SAP HANA : Future of Data Warehousing and Bigdata Analytics

SAP HANA

Webinar will discuss about: History and present of SAP Business Model. Overview of Technology underlying SAP HANA (In Memory Computing) , Bigdata, Space for Analytics. SAP HANA Modelling Environment (Architecture + Setting up Environment). Data warehousing Models (Star schema + concept of master data). Basic Graphical Views (attribute, analytical and calculation Views). Data base operation in Hana tool.
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Why is a Central Analytics Team Vital to a Self-Service Data Culture?

When your teams are building products for competitive markets and demanding customers, the right insights can make all the difference. Join us for this month’s Coffee Chat webinar to learn how you help your whole organization make better decisions, take faster action—and deliver the kind of experiences that drive revenue, loyalty, and lifetime value.
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Spotlight

Data analytics are used to test controls and validate that business risks are managed. This would generally occur at a point-in-time when an assurance activity is scheduled. Rather than test a number of transactions, the entire population of transactions can be reviewed for greater coverage. Data analytics includes automated tools such as generalised audit software, test data generators, computerised audit programs, specialised audit utilities and computer-assisted audit techniques (CAATs).

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