IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

Data Governance 79

Data Governance Business Objectives Strategy Data Quality 79

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Any metric can and will be abused.

Marketing 362

Marketing Experimentation Metrics Testing 362

Alation

MARCH 14, 2023

It should make data available, maintain data consistency and accuracy, and support data security. Gartner describes it as ‘ a highly dynamic process employed to support the acquisition, organisation, analysis, and delivery of data in support of business objectives ’. Why is a data strategy important?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Alation

NOVEMBER 17, 2022

Becoming data-driven requires that people understand what data-driven means, and that the right people are in place to govern, maintain, and analyse the data. So, let’s start at the beginning of this journey and establish step by step what it means to be truly data-driven. First, what are your business objectives?

Data-driven 52

Data-driven Cost-Benefit Business Objectives Technology 52

IBM Big Data Hub

OCTOBER 20, 2023

Gaining an understanding of available AI tools and their capabilities can assist you in making informed decisions when selecting a platform that aligns with your business objectives. Data extraction: Platform capabilities help sort through complex details and quickly pull the necessary information from large documents.

Machine Learning 75

Machine Learning Manufacturing Cost-Benefit Deep Learning 75

datapine

DECEMBER 11, 2019

SaaS is less robust and less secure than on-premises applications: Despite some SaaS-based teething problems or technical issues reported by the likes of Google, these occurrences are incredibly rare with software as a service applications – and there hasn’t been one major compromise of a SaaS operation documented to date.

Software 314

Software Cost-Benefit Data Processing Data-driven 314