IBM Big Data Hub

JANUARY 25, 2023

In our last blog , we introduced Data Governance: what it is and why it is so important. In this blog, we will explore the challenges that organizations face as they start their governance journey. Organizations have long struggled with data management and understanding data in a complex and ever-growing data landscape.

Data Governance 52

Data Governance Data-driven Strategy Management 52

Cloudera

MARCH 4, 2024

In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. In a good data governance strategy, it is important to define roles that allow the business to limit the level of access that users can have to their strategic data assets.

Metadata 52

Metadata Data Governance Management Finance 52

Cloudera

AUGUST 30, 2022

Data-fuelled innovation requires a pragmatic strategy. This blog lays out some steps to help you incrementally advance efforts to be a more data-driven, customer-centric organization. For example, providers can start by including more real-time data streams that can enhance customer interactions.

Strategy 107

Strategy Data Strategy ROI Cost-Benefit 107

Alation

JANUARY 26, 2023

Data is a key asset for businesses in the modern world. Used correctly, it can improve internal operations, power marketing strategies, and much more. That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. Let’s look at five different ways.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

TDAN

AUGUST 16, 2022

Data Acumen, Literacy, and Culture Data literacy, or data acumen[1] as we like to call it, is increasingly cited as a critical enabler of being a data-driven organization. We set out to do something about that and developed a data acumen quick reference. Using the quick reference, folks […].

Data-driven 52

Data-driven IT Data Quality Data Strategy 52

Andrew White

APRIL 19, 2022

I read with great interest a report from Grant Thornton and the Data Foundation that is ‘state of the union’ for the US Federal Data Strategy. Here it is: On the maturation of data governance in U.S. There is additional insight in this article: Federal CDOs Seek More Guidance on Government’s Data Strategy.

Data Strategy 52

Data Strategy Strategy Data Governance Reporting 52

DataKitchen

FEBRUARY 18, 2022

This paper will focus on providing a prescriptive approach in implementing a data pipeline using a DataOps discipline for data practitioners. Data is unique in many respects, such as data quality, which is key in a data monetization strategy. Data governance is necessary in the enforcement of Data Privacy.

Data Quality 130

Data Quality Machine Learning Business Intelligence Data Governance 130

Octopai

JUNE 24, 2019

There are a number of scenarios that necessitate data governance tools. Businesses operating within strict industry regulations, utilizing analytics software, and/or regularly consolidating data in key subject areas will find themselves looking into data governance tools to help them achieve their goals.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 125

Data Architecture Data Warehouse Statistics Visualization 125

TDAN

JUNE 18, 2019

Part one of this series addressed the structure of the Non-Invasive Data Governance Framework. I refer to the row labels as the Levels or perspectives of the organization and the column labels as the Core Components of a […]. In part two, I detail each of the labels on the rows and columns of the framework.

Data Governance 45

Data Governance Metadata Data Strategy Business Intelligence 45

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 82

Data Lake Data Governance Data Architecture Data Warehouse 82

CIO Business Intelligence

NOVEMBER 16, 2022

The company employs 69,000 around the world as well and Danielle Brown, the company’s SVP and CIO, has a unique perspective on how best to lead the company’s digital transformation strategy. I’ve heard it referred to as the lattice. On the enterprise data strategy: I am a self-admitted data geek.

IT 133

IT Modeling Digital Transformation Data Governance 133

DataKitchen

JUNE 12, 2023

Today we have had over 20,000 signatures , millions of page views, and copycat clones, and it is frequently used as a reference guide. For example, just a few weeks ago, Microsoft announced data fabric, and John Kerski used it to frame up the discussion of how Microsoft data fabric supports DataOps principles.

Testing 130

Testing Data Lake Dashboards Data Science 130

TDAN

APRIL 4, 2023

To talk with Bob Seiner is to talk with a friend and a personal reference in the field of data management. The fact that I have collaborated with him in the translation of his first book, Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success, into Spanish is a source of pride. After […]

Data Governance 52

Data Governance Management Metadata Data Strategy 52

TDAN

OCTOBER 1, 2019

One could argue it has become cliché to make references to the enormous significance and proliferation of data globally. Human and machine generated data is increasing even more rapidly at 10x that of traditional business data [1]. By […].

Data Governance 45

Data Governance IT Data Strategy Business Intelligence 45

Alation

JULY 19, 2021

Yes, we’re talking about metadata, or information that describes other data. For enterprise data, metadata, and effective metadata management , is a critical component of a good data management strategy. In today’s world, metadata management best practices call for a data catalog. Reference information.

Metadata 105

Metadata Management Data Governance Machine Learning 105

erwin

MARCH 30, 2020

To do this, the consortium will need the ability to automatically scan and catalog the data sources and apply strict data governance and quality practices. Unraveling Data Complexities with Metadata Management. Data profiling for data assessment, metadata discovery and data validation.

Metadata 122

Metadata IT Data Governance Data Quality 122

CIO Business Intelligence

DECEMBER 7, 2023

Along the way, business leaders in every industry have been scrambling to develop their generative AI strategies, address potential risks, and figure out the best next action while trying to stay one step ahead of the competition. Likewise, they realize that human talent will be central to success.

Insurance 60

Insurance Experimentation Finance Data Governance 60

CIO Business Intelligence

MAY 16, 2024

For us, the IT strategy to support digital innovation is based on several levels, with a different time perspective,” says Anna Giardini, CIO of private hospital operator ICS (Istituti Clinici Scientifici privati) Maugeri SpA, Società Benefit. More than green IT This broad understanding of sustainability changes the role of the CIO.

Digital Transformation 86

Digital Transformation Data-driven Cost-Benefit Management 86

Octopai

JUNE 19, 2023

In an era where data is often referred to as the new oil, having a well-organized and easily accessible data catalog is no longer a luxury but a necessity as organizations deal with the deluge of too much data (data bloatedness) coming from every system and landscape.

Metadata 88

Metadata Data Governance Measurement Risk Management 88

datapine

SEPTEMBER 29, 2022

Effective DQM is recognized as essential to any consistent data analysis, as the quality of data is crucial to derive actionable and – more importantly – accurate insights from your information. There are a lot of strategies that you can use to improve the quality of your information.

Data Quality 241

Data Quality Metrics Data-driven Management 241

TDAN

JULY 19, 2022

In reference to the prior column on enterprise data management and high level lego framework, this column reviews in detail the foundational layer of Organization Mission, Level 1.

Strategy 52

Strategy Enterprise Management Modeling 52

IBM Big Data Hub

DECEMBER 14, 2023

Cyber resiliency refers to an organization’s ability to prepare for, respond to, and recover from cyber threats while maintaining the continuity of operations. It encompasses a holistic approach that focuses on resilience at every level of an organization’s infrastructure, from applications and networks to data and people.

Risk 78

Risk Measurement Business Objectives Optimization 78

AWS Big Data

APRIL 19, 2023

Encounter 4 appears to refer to the customer with ID 8, but the email doesn’t match, and no Customer_ID is given. Conclusion Data-driven organizations are transitioning to a data product way of thinking. Utilizing strategies like data mesh generates value on a large scale.

Technology 82

Technology Data-driven Machine Learning Sales 82

Alation

DECEMBER 9, 2021

Then, we’ll dive into the strategies that form a successful and efficient cloud transformation strategy, including aligning on business goals, establishing analytics for monitoring and optimization, and leveraging a robust data governance solution. How to Develop a Cloud Transformation Strategy.

Cost-Benefit 52

Cost-Benefit Data Governance Optimization Data Processing 52

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

Ontotext

SEPTEMBER 1, 2023

LLMs in particular have remarkable capabilities to comprehend and generate human-like text by learning intricate patterns from vast volumes of training data; however, under the hood, they are just statistical approximations. An LLM, on the other hand, is a neural network model built by processing text data.

Risk 52

Risk Modeling Data Quality Data Governance 52

erwin

JULY 11, 2019

Supporting and reference documentation. Data usage. It requires robotics to cross-reference mass amounts of information, never before integrated to support effective decision-making. Compliance, project and initiative information.

Digital Transformation 106

Digital Transformation Modeling Data Governance Visualization 106

erwin

AUGUST 20, 2020

In the age of data-driven business, the most common EA use cases are: Digital Transformation. Data Governance. EA provides context and perspective as to how and where data is used, including the applications, policies and processes that leverage it. Big Data Adoption. Application Portfolio Management.

Enterprise 140

Enterprise Cost-Benefit Risk Data Governance 140

TDAN

OCTOBER 18, 2022

“Technical debt” refers to the implied cost of future refactoring or rework to improve the quality of an asset to make it easy to understand, work with, maintain, and extend.

Software 94

Software Data Architecture IT Data Quality 94

Alation

AUGUST 9, 2022

But in the four years since it came into force, have companies reached their full potential for data integrity? But firstly, we need to look at how we define data integrity. What is data integrity? Many confuse data integrity with data quality. This strategy should also consider data security.

Data Integration 52

Data Integration Data Quality Measurement Strategy 52

AWS Big Data

SEPTEMBER 25, 2023

Solution overview As we discussed in the previous section, ExampleCorp has multiple Redshift data warehouses: one enterprise data warehouse and two downstream Redshift data warehouses. Each data warehouse has different workloads, SLAs, and concurrency requirements. ID Service class 1–4 Reserved for system use.

Management 94

Management Data Warehouse Metrics Dashboards 94

Alation

APRIL 18, 2023

Top use cases for data profiling Data governance Data governance describes how data should be gathered and used within an organization, impacting data quality, data security, data privacy , and compliance.

IT 52

IT Metadata Data Quality Data Governance 52

erwin

JUNE 26, 2020

If you’re serious about a data-driven strategy , you’re going to need a data catalog. Organizations need a data catalog because it enables them to create a seamless way for employees to access and consume data and business assets in an organized manner. Business Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

erwin

JUNE 11, 2020

Data Intelligence is the analysis of multifaceted data to be used by companies to improve products and services offered and better support investments and business strategies in place. Big IT companies even have off-the-shelf data analytics software ready to be configured by a company to their needs.

Key Performance Indicator 103

Key Performance Indicator KPI Data-driven Machine Learning 103

Cloudera

DECEMBER 3, 2021

An AI system trained on data has no context outside of that data. There is no moral compass, no frame of reference of what is fair unless we define one. Another function of a centralised governance capability is to perform quality control spot-checks and assess model performance and suitability based on prior data and problems.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102