Business Objectives Data Governance Data-driven Document 
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.
erwin
JULY 12, 2019
In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). Complexity. Five Steps to GDPR/CCPA Compliance.
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Alation
NOVEMBER 17, 2022
But what does it mean for an organisation to be truly data-driven? What foundation needs to be in place at the start, and what journey does an organisation need to embrace to benefit from the forensic insights their data can reveal? Step 1 – Be clear about your business objectives. Being profitable (19 times).
CIO Business Intelligence
FEBRUARY 7, 2024
As enablers for the integration of data and business services across platforms, APIs are very aligned with current tech trends,” says Antonio Vázquez, CIO of software company Bizagi. Ajay Sabhlok, CIO and CDO at zero trust data security company Rubrik, Inc.,
CIO Business Intelligence
OCTOBER 24, 2023
Business drivers for the first wave of digital transformation through 2020 targeted growth, data capabilities, cloud migration, and delivering competitive technology capabilities. With generative AI now a firm digital transformation priority , 2023-24 will mark the beginning of an AI-driven transformation era.
Alation
MARCH 14, 2023
Data gathering and use pervades almost every business function these days — and it’s widely acknowledged that businesses with a clear strategy around data are best placed to succeed in competitive, challenging markets such as defence. What is a data strategy? Why is a data strategy important?
O'Reilly on Data
JULY 28, 2020
It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Agreeing on metrics. This is particularly true for AI products.
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