Sisense

SEPTEMBER 3, 2020

Besides strong technical skills (for instance, use of Hadoop, programming in R and Python , math, statistics), data scientists should also be able to tackle open-ended questions and undirected research in ways that bring measurable business benefits to their organization. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

CIO Business Intelligence

AUGUST 7, 2023

According to Rocket Software’s survey, nearly half of respondents (42%) noted that they think about IT risk daily (31%) and even multiple times a day (11%). Sixty-three percent of IT leaders even measure success within their IT organization by their ability to reduce risk.

Risk 87

Risk IT Management Risk Management 87

datapine

FEBRUARY 22, 2022

1) What Is A Business Intelligence Strategy? 4) How To Create A Business Intelligence Strategy. Odds are you know your business needs business intelligence (BI). Over the past 5 years, big data and BI became more than just data science buzzwords. Table of Contents.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

datapine

AUGUST 29, 2022

At 156 pages on Kindle, this is a book you could finish in one (long) sitting if you were so inclined, and that you can also use as an inspiration when you work on your business intelligence strategy. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Octopai

JULY 12, 2020

GIGO may be an old refrain, but it likely gave rise to the concept of what we know as ‘business intelligence’. BI has helped enhance a company’s ability to process large amounts of data. Perhaps most frustrating for FCSA was the major data-quality issues that arose due to manual, error-prone data processing.

Data Warehouse 58

Data Warehouse Data Quality Metadata Risk Management 58

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

AWS Big Data

AUGUST 14, 2023

When are data products deprecated, and who is accountable for the consequences to their consumers? How do we define “risk” and “value” in the context of data products, and how can we measure this? Whose responsibility is it to justify the existence of a given data product?

Management 76

Management Risk Measurement Optimization 76