The Role Of Data Warehousing In Your Business Intelligence Architecture

datapine

Effective decision-making processes in business are dependent upon high-quality information. What Is Data Warehousing And Business Intelligence? BI Architecture Framework In Modern Business. Now we approach the data warehousing and business intelligence concepts.

Metadata is Like Body Language

TDAN

The Nonverbal Dilemma Nonverbal communication is composed of body gestures and vocal inflections. The words you speak are a small fraction of communication.

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Metadata Management, Data Governance and Automation

erwin

According to IDC’s “Data Intelligence in Context” Technology Spotlight sponsored by erwin, “professionals who work with data spend 80 percent of their time looking for and preparing data and only 20 percent of their time on analytics.”. Can the 80/20 Rule Be Reversed?

How Metadata Makes Data Meaningful

erwin

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 are these rampant and often uncontrolled projects to collect metadata properly motivated?

How Metadata Makes Data Meaningful

erwin

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 are these rampant and often uncontrolled projects to collect metadata properly motivated?

Business Glossaries and Metadata: Data Governance May Require a Village

TDAN

Is adoption by the business an issue for you? Data Governance occurs best when done in conjunction with the business processes and not as a “bolt on”/additional activity. Is your organization struggling to succeed with your Data Governance program?

What Role Does Data Mining Play for Business Intelligence?

Jet Global

In the modern era, businesses are continually looking for a competitive advantage—something that will allow them to deliver goods or services at a lower cost, higher quality, and faster speed than their competitors. Data Mining and Business Intelligence.

Requirements for Data Governance

TDAN

Recording requirements for success is an important first step toward demonstrating the value of a Data Governance program. Practitioners know that Data Governance requires planning, resources, money and time and that several of these objects are in short supply.

Data Management 20/20: The Trinity of the Business Glossary

TDAN

Essential Components forthe Business/IT Lexicographer Today’s organizations often struggle with how poorly their information systems perform.

Practical Points from the DGPO: Dawn of Self-Service BI Governance

TDAN

It seems that Self-Service BI is finally taking off. After decades of hope, hype, over-promising, and disappointment, technology that businesspeople can use is finally becoming available, albeit with some level of data literacy. But before we cheer for this success a little caution is in order.

Deep Learning Can Make a Difference

TDAN

Deep learning, as defined by MathWorks, is a system of artificial intelligence that is built around learning by example. Multiple industries have already understood the benefits that deep learning brings to their operational capabilities.

The Non-Invasive Data Governance Framework – The Details

TDAN

The third and final part of the Non-Invasive Data Governance Framework details the breakdown of components by level, providing considerations for what must be included at the intersections.

Data Governance Roles and Responsibilities

TDAN

Roles and responsibilities are the backbone of a successful information or data governance program.

Defeat Your Data Demons

TDAN

The stories you hear on the news often mention how this person or that person was battling their demons. Alcoholism, drug addiction, compulsive behaviors like gambling … Demons take many forms. Demons almost never result in good things happening.

Benefits of Data Dictionary Tools for Enterprise Metadata Management

Octopai

Like any good puzzle, metadata management comes with a lot of complex variables. There’s a distinction between a data dictionary and a business glossary. A data dictionary is a tool that organizes and describes different variables indicated by metadata associated with a dataset.

Data Management 20/20: Rationalizing Complex Business Terms

TDAN

Common Business Term Problem Symptoms Much of the information assets of an organization are captured in business glossaries which are the compendiums of business terms, their definitions and other properties that form the organization’s core business vocabulary.

All in the Data: CDOs Should Be Asking “How” … and Not “Why”

TDAN

The secret lies with Data Governance. The Chief Data Officer (or whoever the Data Czar is at your organization) needs to get past, and I mean way past, the “Why is Data Governance important?” or “Why do we need Data Governance?” questions if they are ever going to be successful czar-ing the data. Rather, the […].

Data is Risky Business: Call for Compulsory Ethics

TDAN

In our book, Ethical Data and Information Management, Katherine O’Keefe and I look at the relationship between the Ethic of Society, which today finds expression this morning, in a report from a UK Parliamentary Committee setting out their findings against Facebook and Cambridge Analytica.

Data Dictionary vs. Business Glossary

TDAN

Let’s take “data dictionary” and “business glossary” for […]. Enterprises today are focused on ensuring robust data governance, and are exploring different tools and approaches to support their efforts.

Data Management 20/20: Business Glossary Best Practices

TDAN

Suppose you need to make some business decisions based on the number of […]. It’s all about communication. Everyone talks about collecting, storing, and analyzing data but how do you make use of this data if you cannot understand it?

All in the Data: What Makes a Data Steward?

TDAN

I recently read a blog that mocked my statement that “everybody is a data steward” and explicitly negated the fact that “everyone who uses data should be a data steward.” I have to tell that blogger that they are wrong.

To Own or Not to Own Data

TDAN

To own data or not to own data, that is the question. This question comes up often when I am speaking with clients or groups of people during my Data Governance webinars and conference presentations.

All in the Data: Calm Management’s Fears About Data Governance

TDAN

Wouldn’t it be great if you could simply put structure around how your organization governs your data without throwing a lot of money and resources at the problem? The truth is you can. It’s all in the data.

Common Data Modeling Mistakes and Their Impact

TDAN

Although data modeling has been around for over 30 years, it ranks among the top areas from which database application problems arise. Moreover, the severity of the problems ranges from totally incorrect functionality to freakishly miserable performance.

Big Data Influence on Restaurants and Catering

TDAN

The restaurant and catering sector is one of the largest industries which serves the expectations of millions daily. While everyone visits establishments like restaurants with their own sets of expectations, it is up to the players in this sector to ensure those expectations are being met.

The Non-Invasive Data Governance Framework – The Framework Structure

TDAN

The following paper is the first of a three-part series that describes the Non-Invasive Data Governance Framework. The framework was developed and is implemented by Robert S. Seiner of KIK Consulting & Educational Services (KIKconsulting.com) and The Data Administration Newsletter (TDAN.com).

Measure Twice, Cut Once: How the Right Data Modeling Tool Drives Business Value

erwin

In today’s hyper-competitive, data-driven business landscape , organizations are awash with data and the applications, databases and schema required to manage it. Improve business processes for operational efficiency and compliance.

One Data Governance for All

TDAN

Maybe you are one of those that believe that there is something called Master Data Governance, Information Governance, Metadata Governance, Big Data Governance, Customer [or insert domain name here] Data Governance, Data Governance 1.0 – 2.0 – 3.0, […].

Tales & Tips from the Trenches: Distinguish Graph DBs from Other DBs

TDAN

Big Data Columns Big Data News, Articles, & Education Business Intelligence Columns Business Intelligence News, Articles, & Education Data Architecture Columns Data Columns Data Education Data Modeling Columns Data Modeling News, Articles, & Education Data Strategy Columns Data Strategy News, Articles, & Education Data Topics Metadata Management Columns Metadata Management News, Articles, & Education graph databases oneil RDBMS.

Trends in Data Management and Analytics

TDAN

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way.

Metadata Management Means Different Things to Different Organizations

Octopai

These processes often rely on humans performing manual discovery and documentation tasks for: – Metadata management – ETL specifications – Report definitions – Reporting errors – Changes to calculations …and many other aspects of the data environment.

Five Benefits of an Automation Framework for Data Governance

erwin

Often these enterprises are heavily regulated, so they need a well-defined data integration model that helps avoid data discrepancies and removes barriers to enterprise business intelligence and other meaningful use. Governing metadata. Supports a wide spectrum of business needs.

The Non-Invasive Data Governance Framework – The Levels and Components

TDAN

Part one of this series addressed the structure of the Non-Invasive Data Governance Framework. In part two, I detail each of the labels on the rows and columns of the 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 […].

DAMA International Community Corner: Announcements & New Chapters

TDAN

Welcome to DAMA Corner, a source of information for data management professionals here in TDAN.com, an industry-leading publication for people interested in learning about data administration, data management disciplines, and best practices. Each column provides an update on the professional organization DAMA International, and an opportunity to share your experience with other professionals that are passionate about data! […].

Oracle Analytics Server (OAS) vs Oracle Analytics Cloud (OAC)

Perficient Data & Analytics

With OAS, like with OBIEE, metadata configuration only happens though the Client Administration Tool and are saved in the RPD file. The OAC thin client modeler offers an easier way to set up metadata but doesn’t offer all the features that are possible with the Client Administration Tool.

Oracle Analytics Server to Replace OBIEE

Perficient Data & Analytics

Oracle Analytics Server (OAS) is the latest Oracle release to supersede Oracle Business Intelligence Enterprise Edition (OBIEE). The migration bundle includes the repository (rpd), catalog and security metadata, and several configuration files.

The 12 Rules of DataOps to Avert a DataOops

Kirk Borne

I was part of a team advising a large organization in how to design and implement an enterprise analytics solution group for the organization’s full end-to-end business activities. Honor business value above all other goals. Written by Dr. Kirk Borne.

Keynote and Session highlights at ASG Evolve19

Jen Stirrup

I’m particularly interested in learning more about metadata management. As I’ve written previously, I believe that metadata management is often overlooked in data science. I’m looking forward to seeing how businesses can securely use data to make better business decisions faster, and compliance teams can reduce data related risks and resolve any data problems. business intelligence data governance

The Rule of Least Power in Data Analytics – Part 2

Kirk Borne

In this part, you’ll learn about four examples that are highly relevant to today’s data-driven business goals. PERSPECTIVES big data analysis business intelligence Data Minds Kirk Borne

ROI 86

Data Lineage Tools: How BI Managers Are Using Them – Straight From the Horse’s Mouth

Octopai

If you’re in the Business Intelligence world, there is a chance that you and I had a brief chat about metadata. In my many encounters with BI professionals, I always start by asking what use case relating to metadata management and data lineage is most challenging to their team.

Convergent Evolution

Peter James Thomas

Once the output of Data Science began to be used to support business decisions, a need arose to consider how it could be audited and both data privacy and information security considerations also came to the fore. This required additional investments in metadata.

Power BI + Azure Data Lake = Velocity & Scale to your Analytics

Perficient Data & Analytics

The biggest challenge Business Analysts and BI developers have is the need to ingest and process medium to large data sets on a regular basis. The Common Data Model (CDM) provides a shared data language for business and analytical applications to use.

What Will Enterprise Data Lineage Look Like in 2020?

Octopai

Data lineage management, once a time-consuming process of manual data tracking used only in times of crisis, has been transformed by automation into an essential tool for making informed business decisions. Metadata Management Automation Increases Accuracy.