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The Business Intelligence Market – What’s Old is New

In(tegrate) the Clouds

As the data visualization, big data, Hadoop, Spark and self-service hype gives way to IoT, AI and Machine Learning, I dug up an old parody post on the business intelligence market circa 2007-2009 when cloud analytics was just a disruptive idea. Ad hoc query, data mining, information I’m still not finding.

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Knowledge

Occam's Razor

Convert Data Skeptics: Document, Educate & Pick Your Poison. Data Mining And Predictive Analytics On Web Data Works? Web Analytics Data Sampling 411. Six Data Visualizations That Rock! The Awesome Power of Visualization 2 -> Death and Taxes 2007. 2007 Predictions: Web Analytics.

KPI 124
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Crystal Reports: Alternatives and Comparison with FineReport

FineReport

It can integrate up to twelve formats of data sources, and create dynamic reports. . SAP acquired Crystal Reports in 2007. Compared to reporting tools, they can realize data forecast thanks to OLAP analysis and data mining technologies. The latest version released is Crystal Reports 2016. Download FineReport.

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Crystal Report: Alternatif dan Perbandingannya Dengan FineReport

FineReport

Crystal Report dapat mengintegrasi sampai dengan 12 format data source dan membuat laporan yang dinamis. SAP mengakuisisi Crystal Report di tahun 2007. Dibandingkan dengan software serupa lainnya, software-software ini dapat memperkirakan data karena teknologi analisis OLAP dan data mining-nya. Download FineReport.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Figure 4: Visualization of a central composite design. Springer New York, 2007. [8] Improving the sensitivity of online controlled experiments by utilizing pre-experiment data. Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, WSDM ’13, page 123–132, New York, 2013. [28]

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Misleading Statistics Examples – Discover The Potential For Misuse of Statistics & Data In The Digital Age

datapine

With the COVID-19 pandemic, the general public was forced to consume scientific information in the form of data visualizations to stay informed about the current developments of the virus. Here they speak about two use-cases in which COVID-19 data was used in a misleading way. 3) Data fishing. But this didn’t come easy.