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

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

IBM Big Data Hub

JUNE 30, 2022

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. The evolution of a multi-everything landscape, and what that means for data strategy.

Data Strategy 57

Data Strategy Strategy Business Objectives Data-driven 57

Anmut

JUNE 9, 2023

Data governance roles are positions within an organisation that ensure data is managed and used effectively. Just like companies use corporate governance to run the business and make the most of their assets, these roles are critical for managing data as an asset and maximising its value.

Data Governance 52

Data Governance Cost-Benefit Metadata Strategy 52

Cloudera

AUGUST 30, 2022

Our experience so far reveals firms are still in the early stages of understanding the operational model and the total cost of ownership related to data platforms deployed in the cloud compared to on-premise deployments. In some cases, firms are surprised by cloud storage costs and looking to repatriate data.

Strategy 102

Strategy Data Strategy ROI Cost-Benefit 102

TDAN

DECEMBER 1, 2021

Migrating data to the public cloud offers a wide range of benefits for enterprises; data teams can more easily access their data, write, and test data science models, evaluate new data platforms and test applications, run POCs, and deploy in production.

Data Governance 83

Data Governance Testing Data Science Enterprise 83

Cloudera

MARCH 25, 2021

This will surely cause headaches for organizations with operations in multiple states, each with their own data privacy regulations. Probably more well known, the EU’s GDPR serves as a model for much of the new data privacy legislation coming forward. Financial institutions and insurers understand the benefits of more data.

Data Strategy 65

Data Strategy Strategy Enterprise Insurance 65

TDAN

JULY 4, 2023

In today’s rapidly changing and advancing world of artificial intelligence (AI), generative AI, and large language models (LLMs), data has become the lifeblood of innovation. Data fuels algorithms, powers decision-making processes, and shapes the future impact of technology.

Data Governance 64

Data Governance Modeling Technology Data Strategy 64

Cloudera

APRIL 18, 2024

With the arrival of the latest AI-powered technologies like large language models (LLMs) and generative AI (GenAI), there’s a vast amount of opportunities for innovation, growth, and improved business outcomes right around the corner. All of that technology, though, depends on data to be successful.

Analytics 92

Analytics Metadata Data Strategy Optimization 92

CIO Business Intelligence

APRIL 6, 2022

For decades organizations chased the Holy Grail of a centralized data warehouse/lake strategy to support business intelligence and advanced analytics. That’s not to say that a decentralized data strategy wholly replaces the more traditional centralized data initiative — Maccaux emphasizes that there is a need for both.

Data Strategy 52

Data Strategy Strategy Internet of Things Data Warehouse 52

Anmut

MARCH 22, 2023

Data maturity models are a crucial step for any organisation looking to improve their data, informing if your current data practices are helping, or holding back, your business. ? Click the links below to navigate to different sections What are data maturity models? Why do we need data maturity models?

Measurement 52

Measurement Modeling Data Quality Data Governance 52

TDAN

AUGUST 15, 2023

Anyone who knows me well knows that I like to build models with Legos as a diversion from my “data-ly” life. I was never fond of Legos when I was young, but started my Lego excursion when I saw a bright yellow Lego Ford Mustang kit that I had to have. Several years later, I […]

Data Governance 52

Data Governance Modeling Metadata Data Strategy 52

TDAN

APRIL 30, 2019

Roles and responsibilities are the backbone of a successful information or data governance program. To communicate effectively […].

Data Governance 79

Data Governance Data Quality IT Metadata 79

TDAN

AUGUST 15, 2023

Artificial Intelligence (AI), Machine Learning (ML) and Large Language Models (LLM) have turned the world on its head. From finance to manufacturing to pharmaceuticals to retail, every industry is jumping on the AI/ML bandwagon. And for good reason. AI/ML has the ability to improve efficiency, drive automation, and shorten delivery cycles.

Data Governance 52

Data Governance Manufacturing Machine Learning Finance 52

CIO Business Intelligence

NOVEMBER 16, 2022

On the enterprise data strategy: I am a self-admitted data geek. When you leverage internal data, you need governance around that data. Our priority is around delivering product innovation and having that digital twin or that digital thread where data is fundamental. The two are extremely important.

IT 131

IT Modeling Digital Transformation Data Governance 131

TDAN

APRIL 18, 2023

For the Enterprise Data Management Council (EDMC), I recently concluded a detailed comparison and mapping of the DMM to the DCAM with the Council’s Product Manager, employing the Soladatus modeling tool with its robust model mapping features. In this column, […]

Modeling 64

Modeling Management Enterprise IT 64

TDAN

JUNE 20, 2023

These days, there is much conversation about the necessity of the data model. The data model has been around for several decades now and can be classified as an artifact of an earlier day and age. But is the data model really out of date? And exactly why do we need a data model, anyway? […]

Modeling 52

Modeling Metadata Data Strategy Data Governance 52

CIO Business Intelligence

JANUARY 22, 2024

Since the introduction of ChatGPT, the healthcare industry has been fascinated by the potential of AI models to generate new content. While the average person might be awed by how AI can create new images or re-imagine voices, healthcare is focused on how large language models can be used in their organizations.

Unstructured Data 93

Unstructured Data Digital Transformation Data Strategy Modeling 93

IBM Big Data Hub

APRIL 8, 2024

Gartner has estimated that 80% of organizations fail to scale digital businesses because of outdated governance processes. Data is an asset, but to provide value, it must be organized, standardized and governed. The new company’s data model is completely different from the original company.

Data-driven 59

Data-driven Management Data Governance Strategy 59

erwin

JANUARY 3, 2019

With this in mind, the erwin team has compiled a list of the most valuable data governance, GDPR and Big data blogs and news sources for data management and data governance best practice advice from around the web. Top 7 Data Governance, GDPR and Big Data Blogs and News Sources from Around the Web. . —

Data Governance 53

Data Governance Big Data Data-driven Data Processing 53

TDAN

NOVEMBER 3, 2020

Data governance is considered an oversight activity for work pertaining to the creation and management of data. That is, what are the policies, procedures, roles, and accountability around data assets. Data governance does […].

Management 69

Management Data Governance Modeling Data Quality 69

CIO Business Intelligence

JUNE 14, 2022

Of course, building a vision and culture around data that gets your company to that point is the trick. The first step, according to EY, is to adopt a visionary core data strategy. Such a strategy should connect how data will inform, support, and drive an organization’s short- and long-term strategic business plans.

Data Transformation 145

Data Transformation Data-driven Data Strategy Strategy 145

Rocket-Powered Data Science

OCTOBER 16, 2020

Be sure to listen to the full recording of our lively conversation, which covered Data Literacy, Data Strategy, Data Leadership, and more. The data age has been marked by numerous “hype cycles.” We build models to test our understanding, but these models are not “one and done.” The Age of Hype Cycles.

Digital Transformation 142

Digital Transformation Experimentation Data Strategy Strategy 142

CIO Business Intelligence

AUGUST 2, 2023

Ryan Snyder: For a long time, companies would just hire data scientists and point them at their data and expect amazing insights. That strategy is doomed to fail. The best way to start a data strategy is to establish some real value drivers that the business can get behind.

Manufacturing 93

Manufacturing Data Architecture Strategy Data Strategy 93

TDAN

NOVEMBER 2, 2021

As proponents of Lean Thinking, we view corporations as data factories that produce information for operations, reporting, and financial modeling. We treat data as inventory, data management as manufacturing, and business output as finished goods. Anything […].

Data Governance 52

Data Governance Operational Reporting Manufacturing Risk 52

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 129

Data Architecture Data Warehouse Statistics Visualization 129

AWS Big Data

FEBRUARY 27, 2024

Machine learning analytics – Various business units, such as Servicing, Lending, Sales & Marketing, Finance, and Credit Risk, use machine learning analytics, which run on top of the dimensional model within the data lake and data warehouse. This enables data-driven decision-making across the organization.

Data-driven 93

Data-driven Data Lake Data Quality Data Governance 93

Timo Elliott

JANUARY 6, 2022

If storage costs are escalating in a particular area, you may have found a good source of dark data. If you’ve been properly managing your metadata as part of a broader data governance policy, you can use metadata management explorers to reveal silos of dark data in your landscape. Data analysis and exploration.

IT 133

IT Metadata Data-driven Data Governance 133

Cloudera

OCTOBER 19, 2022

For example, concerns about compliance with volatile data protection regulations, the need for multi-cloud capabilities, and the demands of enterprise customers (especially the government) require data architecture options. 2- AI capability drives data monetization. 3- Security and data governance are still the priority.

Optimization 78

Optimization Data Architecture Data Governance Digital Transformation 78

Cloudera

JANUARY 28, 2022

Then there are the more extensive discussions – scrutiny of the overarching, data strategy questions related to privacy, security, data governance /access and regulatory oversight. These are not straightforward decisions, especially when data breaches always hit the top of the news headlines.

Slice and Dice 111

Slice and Dice Cost-Benefit Risk Data Governance 111

CIO Business Intelligence

OCTOBER 24, 2023

As CIOs prepare for the next wave of digital transformation, they must demonstrate shorter-term business impacts from technology investments and achieve larger innovation goals that evolve the organization’s business model. 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

TDAN

SEPTEMBER 3, 2019

The quality of data used in business is more important now than ever before. Accordingly, in order for organizations to deliver good business results, their data must be accurate, and the use of that data must be governed through policy and monitoring. The most […].

Data Governance 63

Data Governance Data Quality Data Strategy Strategy 63

CIO Business Intelligence

JUNE 30, 2023

It’s well acknowledged that data, when used correctly, has the potential to be a strategic growth asset driving innovation – and with the recent developments in large language models (LLM) for AI, data is really having its day in the sun. And we’ll let you in on a secret: this means nailing your data strategy.

Internet of Things 89

Internet of Things Strategy Risk Data Strategy 89

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 80

Data Lake Data Governance Data Architecture Machine Learning 80

CIO Business Intelligence

MAY 2, 2022

Mason, highly skilled in using data to inform transformational changes in a business, will share insights about leading data projects as well as field questions in a live discussion with attendees. Travelers Senior Vice President and Chief Data and Analytics Officer Mano Mannoochahr will discuss creating a data-first culture.

Advertising 93

Advertising Data Governance Insurance Strategy 93

CIO Business Intelligence

JANUARY 5, 2024

We closed three of our own data centers and went entirely to the cloud with several providers, and we also assembled a new data strategy to completely restructure the company, from security and finance, to hospitality and a new website. You mentioned assembling a new data strategy to restructure the company.

IT 108

IT Finance Cost-Benefit Strategy 108

Jen Stirrup

NOVEMBER 15, 2022

Often, this problem can be due to the organization concentrating solely on technology and data. However, organizations can be supported by a synergistic approach by integrating systems thinking with the data strategy and technical perspective. However, the thrust here is not to diminish data science or data engineering.

Data Science 145

Data Science Digital Transformation Data-driven Measurement 145