erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

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). Govern PII “at rest”. Govern PII “in motion”. Complexity.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. But governance is a time-consuming process (for users and data stewards alike).

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

erwin

OCTOBER 31, 2019

Do you know where your data is? What data you have? Add to the mix the potential for a data breach followed by non-compliance, reputational damage and financial penalties and a real horror story could unfold. s Information Commissioner’s Office had levied against both Facebook and Equifax for their data breaches.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

Cloudera

AUGUST 12, 2021

In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. Collecting workforce data as a tool for talent management. Collecting workforce data as a tool for talent management.

Data-driven 107

Data-driven Manufacturing Insurance Risk Management 107

Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Alation

FEBRUARY 10, 2021

The way enterprises implement data governance is changing. In the past, data governance either emphasized exercising tight control over data or fitting people into rigid roles and processes. With both approaches, data governance is a hurdle to productive data & analytics rather than an enabler.

Data Governance 52

Data Governance Data-driven Enterprise Risk 52

erwin

JANUARY 24, 2019

Organizations are responsible for governing more data than ever before, making a strong automation framework a necessity. In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. Governing metadata.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

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? This requires: Data is embedded into the processes of the organisation.

Data-driven 52

Data-driven Cost-Benefit Business Objectives Technology 52

Alation

SEPTEMBER 9, 2021

Banks collect and manage a lot of sensitive data. And, the data collection doesn’t stop there — rich insights like transactions and purchasing information help to round out customer profiles. Data is both the enabler and the competitive advantage behind these experiences.” — Satyen Sangani, CEO and co-founder, Alation.

Data Governance 52

Data Governance Data Strategy Strategy Risk 52

CIO Business Intelligence

DECEMBER 19, 2023

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. As every CIO can attest, the aggregate demand for IT and data capabilities is straining their IT leadership teams.

Digital Transformation 142

Digital Transformation Unstructured Data Machine Learning Risk Management 142

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

CIO Business Intelligence

NOVEMBER 21, 2023

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT.

IT 134

IT Risk Cost-Benefit Risk Management 134

erwin

SEPTEMBER 10, 2020

Not Documenting End-to-End Data Lineage Is Risky Busines – Understanding your data’s origins is key to successful data governance. Not everyone understands what end-to-end data lineage is or why it is important. Data Lineage Tells an Important Origin Story. Who are the data owners?

Data Governance 131

Data Governance Key Performance Indicator Digital Transformation Metadata 131

erwin

APRIL 29, 2020

Data lineage is the journey data takes from its creation through its transformations over time. Tracing the source of data is an arduous task. With all these diverse data sources, and if systems are integrated, it is difficult to understand the complicated data web they form much less get a simple visual flow.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

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.

Digital Transformation 144

Digital Transformation Data-driven Business Objectives Strategy 144

Ontotext

FEBRUARY 12, 2024

Part one of this three-part series discussed the concept of data mesh and explored what it is and why an organization should care. Here, part two provides best practices for data mesh, including practical guidance, challenges, and limitations. Enterprises should identify and adopt specific data mesh elements to achieve velocity.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

erwin

JUNE 14, 2019

Its past successes – and future potential – are well documented, chronicled in the billion-dollar valuations of the frontrunners in the practice. The inherently competitive nature of retail has made the sector a leader in adopting data-driven strategy. This is an important data point for marketing strategy.

Digital Transformation 111

Digital Transformation Data Governance Risk Data-driven 111

erwin

AUGUST 20, 2020

It provides a visual blueprint, demonstrating the connection between applications, technologies and data to the business functions they support. As a practice, EA involves the documentation, analysis, design and implementation of an organization’s assets and structure. Reduced risks and costs. Data Governance.

Enterprise 140

Enterprise Cost-Benefit Risk Data Governance 140

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

erwin

OCTOBER 17, 2019

Architect Everything: New use cases for enterprise architecture are increasing enterprise architect’s stock in data-driven business. it ensures not only access to proper documentation but also current, updated information. The Regulatory Rationale for Integrating Data Management & Data Governance.

Enterprise 106

Enterprise Digital Transformation Data Governance Risk Management 106

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.,

Business Objectives 123

Business Objectives Cost-Benefit Strategy Data-driven 123

Alation

JULY 15, 2022

Data ethics is both an imperative and an opportunity. New regulations covering data privacy and other ethical concerns require that enterprises govern internal data processes according to these new laws. I asked attendees: How often do you think about data ethics? What does data ethics mean to you?

Cost-Benefit 89

Cost-Benefit Data Governance ROI Risk 89

Cloudera

JUNE 22, 2023

These dis-integrated resources are “data platforms” in name only: in addition to their high maintenance costs, their lack of interoperability with other critical systems makes it difficult to respond to business change. The top-line benefits of a hybrid data platform include: Cost efficiency. Simplified compliance. Flexibility.

Cost-Benefit 65

Cost-Benefit Digital Transformation Data Governance Unstructured Data 65

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. Managing metadata should not be a sub-goal of data governance. Quite simply, metadata is data about data.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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. Three Types of Metadata in a Data Catalog.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

erwin

NOVEMBER 13, 2020

Data Security & Risk Management. Data Center Consolidation. Data Governance (knowing what data you have and where it is). For example, a COVID response plan will use EA to document if employees work from home, what their roles are, the projects on which they’re working, and what their schedules are.

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

Alation

OCTOBER 26, 2021

Today’s best-performing organizations embrace data for strategic decision-making. Because of the criticality of the data they deal with, we think that finance teams should lead the enterprise adoption of data and analytics solutions. This is because accurate data is “table stakes” for finance teams.

Finance 52

Finance Data Transformation Enterprise Metrics 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. Managing metadata should not be a sub-goal of data governance. Quite simply, metadata is data about data.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

CIO Business Intelligence

MARCH 8, 2023

According to Infosys research, data and artificial intelligence (AI) could generate $467 billion in incremental profits worldwide and become the cornerstone of enterprises gaining a competitive edge. 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

erwin

MAY 14, 2021

compliance with the General Data Protection Regulation). Accelerating the retrieval and analysis of data —so much of it unstructured—is vital to becoming a data-driven business that can effectively respond in real time to customers, partners, suppliers and other parties, and profit from these efforts.

Modeling 80

Modeling Digital Transformation Data-driven Optimization 80

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Several factors are driving the adoption of knowledge graphs. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

NOVEMBER 9, 2022

Data-informed decision-making is a key attribute of the modern digital business. But experienced data analysts and data scientists can be expensive and difficult to find and retain. Self-service analytics typically involves tools that are easy to use and have basic data analytics capabilities.

Analytics 136

Analytics Slice and Dice Metrics Sales 136

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Fair warning: if the business lacks metrics, it probably also lacks discipline about data infrastructure, collection, governance, and much more.) Agreeing on metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

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?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

IBM Big Data Hub

JULY 7, 2023

Threats to your data are virtually everywhere these days, and too often, data compromises seem almost inevitable. But with a proactive approach to data security, organizations can fight back against the seemingly endless waves of threats. Data breaches can be disastrous for organizations.

Risk 40

Risk Data Governance Data Lake Data-driven 40