datapine

NOVEMBER 27, 2019

Over the past decade, business intelligence has been revolutionized. Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

APRIL 14, 2022

After all, these are some pretty massive industries with many examples of big data analytics, and the rise of business intelligence software is answering what data management needs. However, the usage of data analytics isn’t limited to only these fields. 9) Checking In And Out With Your Smartphone.

Big Data 244

Big Data Recreation/Entertainment Analytics Data-driven 244

Peter James Thomas

AUGUST 13, 2018

Between November and December 2017, I published the three parts of my Anatomy of a Data Function. Eight months is a long time in the data arena and I have now issued an update. Change Data Science to Data Science / Engineering in order to better reflect the continuing evolution of this area.

Data Science 42

Data Science Publishing Analytics IT 42

CIO Business Intelligence

APRIL 15, 2022

In 2017, The Economist declared that data, rather than oil, had become the world’s most valuable resource. Organizations across every industry have been and continue to invest heavily in data and analytics. But like oil, data and analytics have their dark side. The refrain has been repeated ever since.

Analytics 144

Analytics Machine Learning Insurance Testing 144

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Peter James Thomas

AUGUST 12, 2018

Especially for all Business Analytics professionals out there (2009). [7]. See in particular my trilogy: Using historical data to justify BI investments – Part I (2011). Using historical data to justify BI investments – Part II (2011). Why Business Intelligence projects fail” (2009).

Metrics 49

Metrics Statistics Data Quality Measurement 49