AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

CIO Business Intelligence

APRIL 1, 2024

The research cited a lack of talent and skills to work with the technology (62%), unclear AI and GenAI investment priorities (47%), and the absence of a strategy for responsible AI (41%) as the top three obstacles. Reach consensus on strategy. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake.

Data Lake 130

Data Lake Consulting Uncertainty Risk 130

CIO Business Intelligence

MARCH 24, 2023

The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.” Such a framework provides your organization with a holistic approach to collecting, managing, securing, and storing data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

DECEMBER 19, 2023

This year’s technology darling and other machine learning investments have already impacted digital transformation strategies in 2023 , and boards will expect CIOs to update their AI transformation strategies frequently. These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment.

Digital Transformation 142

Digital Transformation Unstructured Data Machine Learning Risk Management 142

IBM Big Data Hub

FEBRUARY 9, 2023

Building a data governance program is an iterative and incremental process Step 1: Define your data strategy and data governance goals and objectives What are the business objectives and desired results for your organization?

Data Governance 84

Data Governance Business Objectives Strategy Data Quality 84

IBM Big Data Hub

NOVEMBER 24, 2023

Application modernization starts with assessment of current legacy applications, data and infrastructure and applying the right modernization strategy (rehost, re-platform, refactor or rebuild) to achieve the desired result. Subsequent phases are build and test and deploy to production.

Cost-Benefit 100

Cost-Benefit Testing Data-driven Enterprise 100

Grooper

APRIL 9, 2020

The heart of digital transformation is data, and organizations without a clear strategy for data curation and enrichment from documents are at risk of failed transformation and missing out on massive revenue opportunities. The way we’ve thought about curating data from documents over the years is fundamentally flawed.

Digital Transformation 65

Digital Transformation Data Quality Enterprise Risk 65

CIO Business Intelligence

APRIL 4, 2024

Webster Bank is following a similar strategy. We’ve established an AI working group with representatives across technology, architecture, data, security, legal, risk, and audit consisting of both technical practitioners and business users to develop AI-use best practices and a governance framework,” says Nafde. Diasio agrees.

Enterprise 133

Enterprise Cost-Benefit Forecasting Strategy 133

Octopai

MAY 15, 2023

Here are some common cost areas where data lineage can be beneficial: Infrastructure and storage costs: Data lineage allows organizations to understand data usage patterns, access frequencies, and data dependencies. Data quality costs: Poor data quality can result in significant costs for organizations.

Data Quality 52

Data Quality Data Governance Data Integration Risk 52

CIO Business Intelligence

APRIL 8, 2024

Digital Athlete draws data from players’ radio frequency identification (RFID) tags, 38 5K optical tracking cameras placed around the field capturing 60 frames per second, and other data such as weather, equipment, and play type. million video frames and documents about 100 million locations and positions of players on the field.

Analytics 105

Analytics Broadcasting Predictive Analytics Metrics 105

datapine

JANUARY 24, 2021

It is not just important to gather all the existing information, but to consider the preparation of data and utilize it in the proper way, has become an indispensable value in developing a successful business strategy. That being said, it seems like we’re in the midst of a data analysis crisis.

IT 317

IT Statistics KPI Data-driven 317

erwin

JANUARY 30, 2020

Constructing a Digital Transformation Strategy: How Data Drives Digital. I’m encouraged by these results as it tells us that enterprises are really beginning to embrace the power of data to shape their organizations. And close to 50 percent have deployed data catalogs and business glossaries.

Data Governance 145

Data Governance Metadata Digital Transformation Cost-Benefit 145

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Data Quality Metadata Data Governance 52

erwin

SEPTEMBER 17, 2020

For example, automatically importing mappings from developers’ Excel sheets, flat files, Access and ETL tools into a comprehensive mappings inventory, complete with auto generated and meaningful documentation of the mappings, is a powerful way to support overall data governance. Data quality is crucial to every organization.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Alation

JULY 15, 2022

I raised the Cambridge Analytica Scandal and pointed out how it is often only when these stories hit the news that people question the ethics behind how companies are using data. Clearly, using private Facebook data collected in a nefarious manner to sway political elections is not ethical. What’s your data strategy?

Cost-Benefit 89

Cost-Benefit Data Governance ROI Risk 89

CIO Business Intelligence

JANUARY 9, 2024

He and his team have created information decks, documents, and presentations that describe the various types of AI and how they can be used and explain how and where AI and machine learning may be useful — and why it’s not the solution to all the problems they have. Can the current state of our data operations deliver the results we seek?

IT 130

IT Risk Cost-Benefit Enterprise 130

erwin

JULY 12, 2019

So it’s important to understand how to use strategic data governance to manage the complexity of regulatory compliance and other business objectives … Designing and Operationalizing Regulatory Compliance Strategy.

Data Governance 110

Data Governance Management Metadata Risk Management 110

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. Define a Metadata Strategy. Defining a metadata strategy requires an organization to consider its data goals.

Metadata 105

Metadata Management Data Governance Machine Learning 105

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

CIO Business Intelligence

MARCH 7, 2024

In my recent column, I delved into the challenges enterprises face in integrating AI into the workplace and outlined strategies for CISOs to monitor or control the use of AI effectively. The benefits of AI for some industries will drive major strategy changes, and the impact will be vast. There is also the concern about using data.

Digital Transformation 72

Digital Transformation Machine Learning Risk Testing 72

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

Alation

AUGUST 17, 2022

Data governance policy should be owned by the top of the organization so data governance is given appropriate attention — including defining what’s a potential risk and what is poor data quality.” It comes down to the question: What is the value of your data? Risk, however, is a different challenge.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

erwin

JANUARY 11, 2019

A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management. The problem usually starts by relying on manual integration methods for data preparation and mapping.

Data Governance 40

Data Governance Risk Metadata Management 40

Ontotext

MAY 2, 2024

They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Jet Global

AUGUST 23, 2021

Used primarily in a strategic context by corporate Finance Divisions and Boards of Directors, financial statements are key documents that must be prepared and produced with care. Manage data from diverse systems. Data quality is a central point for producing quality reports that can be used effectively in decision-making.

Finance 52

Finance Reporting Data Collection Data Quality 52

Jet Global

MAY 1, 2020

Data quality issues. Here’s the ugly truth: Everybody has a data quality problem. This is because people won’t use BI applications that are founded on irrelevant, incomplete, or questionable data. That’s because nothing will highlight data quality issues like seeing them pop up in a dashboard.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

Smart Data Collective

APRIL 29, 2020

A survey from Tech Pro Research showed that 70 percent of organisations already have a digital transformation strategy or are developing one. Solutions for the various data management processes need to be carefully considered. Developing an effective data management strategy that will allow the business to scale should be a priority.

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

Smart Data Collective

APRIL 20, 2022

Errors in data entry might have serious effects if they are not discovered quickly. Human mistake is the most common cause of data entry errors. Since typical data entry errors may be minimized with the right steps, there are numerous data lineage tool strategies that a corporation can follow.

Data Processing 135

Data Processing Data Collection Technology Optimization 135

AWS Big Data

APRIL 19, 2023

Background The success of a data-driven organization recognizes data as a key enabler to increase and sustain innovation. The goal of a data product is to solve the long-standing issue of data silos and data quality. However, today’s data mesh platform contains largely independent data products.

Technology 78

Technology Data-driven Machine Learning Sales 78

CDW Research Hub

AUGUST 12, 2020

What is your organization doing to protect the value of your data? A strong data governance strategy helps ensure that your data is usable, accessible and protected, guaranteeing trust in the quality and consistency of the data. But creating a data governance program is not something you can do overnight.

Data Governance 52

Data Governance Data-driven Dashboards Strategy 52

O'Reilly on Data

JULY 28, 2020

One mid-sized digital media company we interviewed reported that their Marketing, Advertising, Strategy, and Product teams once wanted to build an AI-driven user traffic forecast tool. One strategy for maintaining motivation is to push for short-term bursts to beat a performance baseline. Data Quality and Standardization.

Marketing 362

Marketing Experimentation Metrics Testing 362

Alation

JUNE 2, 2022

Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches. These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Data management can never be a pure, complete process. However, governance processes are equally important.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Cloudera

NOVEMBER 15, 2021

Examples of structured data include the Iris Flower data set where each datum (corresponding to a sample flower) has the same, predefined structure, namely the flower type, and four numerical features: height and width of the petal and sepal. Data curation.

Unstructured Data 85

Unstructured Data Recreation/Entertainment Structured Data Reporting 85

IBM Big Data Hub

JANUARY 8, 2024

Stage 4 – Transformative business strategy A broader range of users are able to access and process event streams to understand their relevance in a business context.  It includes a built-in schema registry to validate event data from applications as expected, improving data quality and reducing errors.

Data-driven 80

Data-driven Management Advertising Enterprise 80

O'Reilly on Data

DECEMBER 12, 2019

Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8].

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

erwin

SEPTEMBER 19, 2019

For years, data governance was the volleyball passed back and forth over the net between IT and the business, with neither side truly owning it. Providing a platform for understanding and governing trusted data assets. Delivering the greatest benefit from data wherever it lives, while minimizing risk.

Data Governance 108

Data Governance Cost-Benefit Enterprise Modeling 108