Ontotext

MAY 2, 2024

Data leaders today are faced with an almost impossible challenge. 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.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

erwin

OCTOBER 8, 2020

So if you’re going to move from your data from on-premise legacy data stores and warehouse systems to the cloud, you should do it right the first time. And as you make this transition, you need to understand what data you have, know where it is located, and govern it along the way. Then you must bulk load the legacy data.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

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

Smart Data Collective

JULY 15, 2021

A data catalog serves the same purpose. By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. You can think of a data catalog as an enhanced Access database or library card catalog system. What Does a Data Catalog Do?

Metadata 127

Metadata IT Data-driven Data Quality 127

erwin

JANUARY 30, 2020

I’m excited to share the results of our new study with Dataversity that examines how data governance attitudes and practices continue to evolve. Defining Data Governance: What Is Data Governance? . 1 reason to implement data governance. Constructing a Digital Transformation Strategy: How Data Drives Digital.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

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

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. Govern PII “at rest”.

Data Governance 110

Data Governance Management Metadata Risk Management 110

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. So questions linger about whether transformed data can be trusted. Data Quality Obstacles.

Data Governance 40

Data Governance Risk Metadata Management 40

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

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

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. Doing Data Lineage Right.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

erwin

APRIL 2, 2021

Organizations are managing more data than ever. With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Who is authorized to use it and how?

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Lineage and chain of custody, advanced data discovery and business glossary.

Testing 131

Testing Metadata Risk Data Science 131

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

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

Smart Data Collective

JULY 27, 2021

Customer relationship management (CRM) platforms are very reliant on big data. As these platforms become more widely used, some of the data resources they depend on become more stretched. CRM providers need to find ways to address the technical debt problem they are facing through new big data initiatives. Visualize the problem.

Big Data 132

Big Data Snapshot IT Dashboards 132

IBM Big Data Hub

SEPTEMBER 20, 2022

Alongside the significant brand reputation risk, there’s also a growing set of data and AI regulations across the world and across industries — like the upcoming European Union AI Act — that companies must adhere to. How do you accommodate for drifting data patterns? How a data fabric enables trustworthy AI.

Metadata 58

Metadata Machine Learning Data-driven Modeling 58

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Operationalizing data to drive revenue CIOs report that their roles are rising in importance and impact. What’s changed?

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

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

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

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

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Data Warehouse Cost-Benefit Metadata Data-driven 82

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

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

Ontotext

JUNE 22, 2023

This will minimize the risk of investing resources in fundamentally wrong assumptions and will give researchers more confidence to choose top targets for validation. Another problem in drug development is that although companies gather a lot of data from multiple databases, they struggle to derive key insights about safety, drugability, etc.

Metrics 52

Metrics Statistics Visualization Metadata 52

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

erwin

MAY 2, 2022

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative. Data modeling basics.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

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. The evolution from Data Governance 1.0

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Alation

JUNE 28, 2022

Collecting and using data to make informed decisions is the new foundation for businesses. The key term here is usable : Anyone can be data rich, and collect vast troves of data. This is where metadata, or the data about data, comes into play. What is a Metadata Management Framework?

Metadata 52

Metadata Management Data Governance Machine Learning 52

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? Common data governance challenges.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. Metadata Is the Heart of Data Intelligence.

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Metadata Management Data-driven Data Architecture 104

Ontotext

FEBRUARY 26, 2024

This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. The answers to these foundational questions help you uncover opportunities and detect risks. Why do risk and opportunity events matter?

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Data-driven Risk Modeling Risk Management 59

DataRobot Blog

MARCH 16, 2023

To deliver on this new approach, one that we are calling Value-Driven AI , we set out to design new and enhanced platform capabilities that enable customers to realize value faster. Best-Practice Compliance and Governance: Businesses need to know that their Data Scientists are delivering models that they can trust and defend over time.

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Experimentation Data-driven Modeling Metadata 98

Alation

MAY 31, 2023

The state of data governance is evolving as organizations recognize the significance of managing and protecting their data. With stricter regulations and greater demand for data-driven insights, effective data governance frameworks are critical. What is a data architect? Ensure data security and compliance.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. Data pipeline orchestration.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

AWS Big Data

JANUARY 22, 2024

The company uses AWS Cloud services to build data-driven products and scale engineering best practices. To ensure a sustainable data platform amid growth and profitability phases, their tech teams adopted a decentralized data mesh architecture. The solution Acast implemented is a data mesh, architected on AWS.

Data-driven 82

Data-driven Advertising Metadata Data Architecture 82

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 84

Cost-Benefit Metadata Data Governance Modeling 84