Remove 2008 Remove Business Intelligence Remove Interactive Remove Metrics
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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

The following are some of the key business use cases that highlight this need: Trade reporting – Since the global financial crisis of 2007–2008, regulators have increased their demands and scrutiny on regulatory reporting. The calculation methodology and query performance metrics are similar to those of the preceding chart.

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Sentry’s David Cramer on bootstrapping a unicorn

CIO Business Intelligence

Sentry was started as an open source project by David Cramer in 2008 to provide monitoring services for application developers. Cramer and co-founder Chris Jennings bootstrapped the company from the ground up, organically growing the business to over 3.5 million developers today. How did that happen?

Software 115
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A perfect match: How tech promoted a small soccer team to the top

CIO Business Intelligence

Thanks to this injection of capital, which allowed it to improve its squad through new hires, Hoffenheim finally reached the Germany’s first division in the 2007-2008 season. Artificial Intelligence, Business Intelligence, Cloud Management, Data Management, Digital Transformation, IT Leadership, SAP

Sales 52
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Data Observability and Monitoring with DataOps

DataKitchen

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. Since 2008, teams working for our founding team and our customers have delivered 100s of millions of data sets, dashboards, and models with almost no errors. Tie tests to alerts.

Testing 214
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Data Science, Past & Future

Domino Data Lab

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Along with your database servers, you had, data warehousing and business intelligence. Then things changed. It was called Hadoop.

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What Is Data Quality and Why Is It Important?

Alation

Artificial Intelligence (AI) and Machine Learning (ML) As more companies implement Artificial Intelligence and Machine Learning applications to their business intelligence strategies, data users may find it increasingly difficult to keep up with new surges of Big Data. Set clearly defined metrics.