Analyze Data Faster with an Open Source Columnar Database

MariaDB

If you are looking for the scalability and performance needed to support interactive, ad hoc analytics on billions of rows – and with SQL – this latest Data Science Central webinar will show you how to combine distributed, columnar storage and parallel query processing with powerful aggregate functions to deliver faster time to insight using modern, on-demand analytics, as well as how to leverage the power of Kafka and Spark connectors to plug into existing data pipelines. We will discuss the architectural overview of columnar databases, share real-world use cases and give a live demonstration.
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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

Accelerating Project Delivery Fast & Data Compliant

Watch our webinar fast data delivery demo for a walkthrough, showing you how to leverage Accelario to increase DevOps velocity, while achieving data compliance and reducing storage costs.
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Strategies for Fitting a Data Lake into a Modern Data Architecture

McKnight Consulting Group

Whether to take data ingestion cycles off the ETL tool and the Data Warehouse or to facilitate competitive Data Science and building algorithms in the organization, the Data Lake a place for unmodeled and vast data will be provisioned widely in 2019. Though it doesn’t have to be complicated, the Data Lake has a few key design points that are critical, and it does need to follow some principles for success. Avoid building the Data Swamp, but not the Data Lake! The tool ecosystem is building up around the Data Lake and soon many will have a robust Lake and Data Warehouse. We will discuss policy to keep them straight, send “horses to courses,” and keep up users’ confidence in the Data Platforms.
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Data Privacy Using AI-Driven Data Catalogs

Do you have your Enterprise’s data privacy under control? Do you know what datasets are sensitive and who has access? Many companies are behind on privacy and regulatory compliance (GDPR, CCPA, etc.). Legacy tools and manual processes are inaccurate and error prone and can force you to choose between delaying data access by months, or increased compliance risk.
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2023 data and analytics trends and predictions

The world of data and analytics is evolving faster than ever before. Those that stay ahead of this change will be able to navigate the challenging economy and dominate the decade of data. Data is driving tectonic shifts across our personal and professional lives, creating new opportunities for organizations - and new challenges. But which trends are truly transformative and which will fail to live up to the hype?
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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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