Alation

SEPTEMBER 9, 2021

Internal and external auditors work with many different systems to ensure this data is protected accordingly. This is where data governance comes in: A robust program allows banks and financial institutions to use this data to build customer trust and still meet compliance mandates. What is Data Governance in Banking?

Data Governance 52

Data Governance Data Strategy Strategy Risk 52

IBM Big Data Hub

MAY 28, 2024

A good DLM process can help organize and structure critical data, particularly when organizations rely on diverse types of data storage. It can also help them reduce vulnerabilities and ensure data is efficiently managed, compliant with regulations, and not at risk of misuse or loss.

Strategy 64

Strategy Measurement Risk Cost-Benefit 64

Alation

JULY 15, 2022

I recently led an online session, Data Monetisation and Governance , looking at the evolution of data governance , defining data ethics (from the Turing Institute ), and touching on the balancing act between using data to monetise (by increasing revenue, decreasing spend, or mitigating risk) and meeting ethical obligations.

Cost-Benefit 89

Cost-Benefit Data Governance ROI Risk 89

erwin

JANUARY 17, 2020

In the modern context, data modeling is a function of data governance. While data modeling has always been the best way to understand complex data sources and automate design standards, modern data modeling goes well beyond these domains to accelerate and ensure the overall success of data governance in any organization.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

CIO Business Intelligence

OCTOBER 24, 2023

Alternatively, they can accelerate transformation by prioritizing force-multiplying initiatives such as aligning data science and data governance programs or improving IT operations with AIops capabilities. Still, certain issues surface time and time again to trouble business outcomes regardless of the strategic objectives.

Digital Transformation 145

Digital Transformation Data-driven Business Objectives Strategy 145

Alation

MAY 10, 2021

Implementing a data catalog enhances an organization’s data management and allows for the democratization of that data But how are data catalogs implemented? In phase one, an enterprise must create a data strategy , which will inform later plans. Build a Data Strategy (Phase One).

Strategy 80

Strategy Enterprise Data Strategy Data Governance 80

AWS Big Data

AUGUST 14, 2023

In the same way, overly restrictive data governance practices that either prevent data products from taking root at all, or pare them back too aggressively (deforestation), can over time create “data deserts” that drive both the producers and consumers of data within an organization to look elsewhere for their data needs.

Management 81

Management Risk Measurement Optimization 81

CIO Business Intelligence

MARCH 8, 2023

Getting there requires process and operational transformation, new levels of data governance and accountability, business and IT collaboration, and customer and stakeholder trust. The reality is many organisations still struggle with the data and analytics foundations required to progress down an advanced AI path.

Enterprise 52

Enterprise Data Governance Data Strategy Testing 52

Alation

MARCH 28, 2023

With data becoming more prevalent in every industry, organisations have to determine how to not only manage it but also drive value from it. The MoD identify three key issues: firstly, that ‘Defence data operates in contractual, technical and behavioural silos’. The defence industry is no exception.

Metadata 52

Metadata Data Strategy Data Quality Strategy 52

Alation

OCTOBER 12, 2021

Like many, the team at Cbus wanted to use data to more effectively drive the business. “Finding the right data was a real challenge,” recalls John Gilbert, Data Governance Manager. We might have found some data but what does it mean? The third challenge was around trusting the data.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

Alation

FEBRUARY 10, 2022

Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Mitigate Security Risk. Content-Based Classification.

Data Governance 52

Data Governance Risk Insurance Strategy 52

Alation

MARCH 21, 2023

What are common data challenges for the travel industry? Some companies struggle to optimize their data’s value and leverage analytics effectively. When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

JULY 28, 2023

Data dependencies – Personal data can be interconnected and intertwined with other data systems, making it challenging to remove specific data without impacting the integrity of functionality of other systems or processes. Ensuring the complete removal of data from all these copies and backups can be challenging.

Snapshot 86

Snapshot Metadata Measurement Data Warehouse 86

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Grooper

AUGUST 19, 2019

Master data management. Data governance. Scoring – i.e. profitability or risk. Structured, semi-structured, and unstructured data. Data pipelines. Banks use analytics to differentiate customers and align product offerings based on credit risk, usage, and other characteristics. Primary keys.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54