datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Birst BI

AUGUST 23, 2018

What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases? Automating data science tasks leaves room to build more AI applications with the same amount of data science resources. Source: Gartner (April 2018).

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

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. 221) to 2019 (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

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

Depict Data Studio

SEPTEMBER 17, 2019

Chris Lysy is a professional data designer and illustrator constantly exploring the overlap between contemporary design practice, digital communications, and data science. David Napoli has worked with data for over 20 years as an analyst, actuary, statistician, research manager, and director. Chris Lysy. Kylie Hutchinson.

Visualization 40

Visualization Consulting Dashboards Reporting 40

Birst BI

MAY 29, 2018

The business intelligence (BI) assembly line is broken, with adoption or utilization rates of only 30 percent in a typical organization, according to Gartner [1]. Figure 3: “Business Intelligence and Analytics” of Davenport and Harris’ Competing on Analytics. The root of the BI problem hasn’t changed.

Slice and Dice 74

Slice and Dice Analytics Business Intelligence Machine Learning 74