INDUSTRY INSIGHTS YOUR PEERS ARE READING
erwin positioned as a Leader in Gartner’s “2019 Magic Quadrant for Metadata Management Solutions”. We were excited to announce earlier today that erwin was named as a Leader in the @Gartner _inc “2019 Magic Quadrant for Metadata Management Solutions.”. MORE
Data Governance Starts With Metadata Management. Like all data governance, healthcare data governance requires tight management and control of metadata —the information about every database, table, column, data warehouse cube, and report element for which the organization is responsible. MORE
The lack of a central metadata repository is a far too common thorn in an organization’s side. A central metadata repository ensures an organization can acknowledge and get behind a single source of truth. MORE
GraphDB: MongoDB Document Store Integration for Large-scale Metadata Management. For example, it’s data generated as a result of text mining algorithms that includes document metadata attributes and annotations with links to the first type of information. MORE
Activating their metadata to drive agile data preparation and governance through integrated data glossaries and dictionaries that associate policies to enable stakeholder data literacy. MORE
Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. Metadata-Driven Automation in the BFSI Industry. Metadata-Driven Automation in the Pharmaceutical Industry. MORE
As I write this, I can almost hear you wail “No, no, we don’t have too much metadata, we don’t have nearly enough! We have several projects in flight to expand our use of metadata.” MORE
End-users are gaining more control of these assets, including the ability to integrate and manipulate them for their own purposes, and being able to select assets based on a relevance criteria not necessarily codified in classic metadata or semantic models. MORE
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? The primary problem is the meaning of data within a certain context where it is used. MORE
If you are just starting out and feel overwhelmed by all the various definitions, explanations, and interpretations of data governance, don’t be alarmed. Even well-seasoned data governance veterans can struggle with the definition and explanation of what they do day to day. MORE
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. MORE
Nutanix introduced the first Hyperconverged platform to the market in 2011. While other Hyperconverged solutions have since come out, what differentiates Nutanix from the other solutions is the focus on implementing a highly scalable, reliable and performant distributed systems architecture MORE
In my last article I suggested that many organizations have approached Data Governance incorrectly using only centralize data governance teams and that approach is not working for many. MORE
When that happens, tens of thousands of people are put at risk for identity theft when their metadata is stolen. What is metadata and how is it used? What Metadata Contains. Metadata is basically a trail of data that is spread out across a network. Metadata typically contains the person’s name, address, phone number, credit card number, email address and even personal or business bank account numbers. Why a Cyber-Criminal Steals Metadata. MORE
Insurance Metadata Management. The keys to proper insurance data managemen t are data governance and metadata management. Data Governance and Metadata Management for the Insurance Industry. Both of these two keys deal with metadata. MORE
Metadata Governance is easiest to understand when you separate the term into its two parts – Metadata and Data Governance. MORE
Metadata is at the heart of every report, dashboard, data warehouse, visualization, and anything else the BI team produces. Without an understanding of the organization’s metadata, the BI team can’t match the data from multiple sources to produce a single view of the business. MORE
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. MORE
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. MORE
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. MORE
For example, it’s data generated as a result of text mining algorithms that includes document metadata attributes and annotations with links to the first type of information. The data includes articles and metadata represented as creative works and annotations between the creative works and DBPedia entities with a complex graph structure also known as reference data. Choose The Best RDF Database for Metadata Management. MORE
Organizations need a real-time, accurate picture of the metadata landscape to: Discover data – Identify and interrogate metadata from various data management silos. Harvest data – Automate metadata collection from various data management silos and consolidate it into a single source. MORE
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. MORE
The importance of metadata. Metadata is best defined as data that characterizes data. Metadata provides the who, what, where, when, why and how of that information. So how does metadata fit in? The easiest way to validate compliance is by using metadata. MORE
BFSI, PHARMA, INSURANCE AND NON-PROFIT) CASE STUDIES FOR AUTOMATED METADATA-DRIVEN AUTOMATION. As stated above, a data governance platform that draws from a single metadata source is even more advantageous here. MORE
There have been a couple of different things converged in my media feeds that highlight a key issue that all data management professionals and leaders in information management need to be conscious of – Group Think. MORE
Metadata management, lately, has emerged as one of the most important practices in organizations. The underlying reason being the increased usage of big data and cloud platforms, and the tendency of information to get scattered in the absence of efficient metadata management. This has necessitated the need for organizations to adopt the best in metadata management practices in order to manage the information assets within the. MORE
Data collection is getting more dispersed and voluminous every day. Corporate entities are constantly merging or splitting, and new lines of business are created in order to meet changing business challenges. MORE
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. MORE
Enterprises today are focused on ensuring robust data governance, and are exploring different tools and approaches to support their efforts. MORE
Is your organization struggling to succeed with your Data Governance program? 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. MORE
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. MORE
Roles and responsibilities are the backbone of a successful information or data governance program. MORE
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. MORE
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 […]. MORE
Organizations faced with the delivery of formal Data Governance or Information Governance programs recognize that there are several challenges they will face when getting started and as the program is operationalized. The challenges are not the same for all organizations. MORE
Nutanix introduced the first Hyperconverged platform to the market in 2011. While other Hyperconverged solutions have since come out, what differentiates Nutanix from the other solutions is the focus on implementing a highly scalable, reliable and performant distributed systems architecture MORE
In data governance terms, an automation framework refers to a metadata-driven universal code generator that works hand in hand with enterprise data mapping for: Pre-ETL enterprise data mapping. Governing metadata. MORE
There’s no question that enterprise application usability has for the most part been left behind MORE
Spelling, pronunciation, and examples of usage are included in the dictionary definition of a word, which is a good example of one of the many uses of metadata, namely to provide a definition, description, and context for data. MORE
The typical notion is that enterprise architects and data (and metadata) architects are in opposite corners. With governance, which sets its fundamental components firmly on data, metadata and infrastructure. It’s time to consider data-driven enterprise architecture. MORE
Metadata Related Topics Sirius Computer Solutions
OCTOBER 16, 2019
The importance of metadata. Metadata is best defined as data that characterizes data. Metadata provides the who, what, where, when, why and how of that information. So how does metadata fit in? The easiest way to validate compliance is by using metadata.
TDAN
MARCH 19, 2019
Metadata Governance is easiest to understand when you separate the term into its two parts – Metadata and Data Governance.
TDAN
SEPTEMBER 17, 2019
In my last article I suggested that many organizations have approached Data Governance incorrectly using only centralize data governance teams and that approach is not working for many.
DataFloq
JULY 2, 2019
Metadata management, lately, has emerged as one of the most important practices in organizations. The underlying reason being the increased usage of big data and cloud platforms, and the tendency of information to get scattered in the absence of efficient metadata management. This has necessitated the need for organizations to adopt the best in metadata management practices in order to manage the information assets within the.
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erwin
FEBRUARY 7, 2019
Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. Metadata-Driven Automation in the BFSI Industry. Metadata-Driven Automation in the Pharmaceutical Industry.
TDAN
SEPTEMBER 3, 2019
As I write this, I can almost hear you wail “No, no, we don’t have too much metadata, we don’t have nearly enough! We have several projects in flight to expand our use of metadata.”
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Octopai
SEPTEMBER 22, 2019
Insurance Metadata Management. The keys to proper insurance data managemen t are data governance and metadata management. Data Governance and Metadata Management for the Insurance Industry. Both of these two keys deal with metadata.
TDAN
JUNE 18, 2019
Is your organization struggling to succeed with your Data Governance program? 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.
Ontotext
JUNE 27, 2019
GraphDB: MongoDB Document Store Integration for Large-scale Metadata Management. For example, it’s data generated as a result of text mining algorithms that includes document metadata attributes and annotations with links to the first type of information.
Smart Data Collective
APRIL 10, 2019
When that happens, tens of thousands of people are put at risk for identity theft when their metadata is stolen. What is metadata and how is it used? What Metadata Contains. Metadata is basically a trail of data that is spread out across a network. Metadata typically contains the person’s name, address, phone number, credit card number, email address and even personal or business bank account numbers. Why a Cyber-Criminal Steals Metadata.
Octopai
JULY 18, 2019
Data Governance Starts With Metadata Management. Like all data governance, healthcare data governance requires tight management and control of metadata —the information about every database, table, column, data warehouse cube, and report element for which the organization is responsible.
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Ontotext
JUNE 27, 2019
For example, it’s data generated as a result of text mining algorithms that includes document metadata attributes and annotations with links to the first type of information. The data includes articles and metadata represented as creative works and annotations between the creative works and DBPedia entities with a complex graph structure also known as reference data. Choose The Best RDF Database for Metadata Management.
Octopai
APRIL 8, 2019
Metadata is at the heart of every report, dashboard, data warehouse, visualization, and anything else the BI team produces. Without an understanding of the organization’s metadata, the BI team can’t match the data from multiple sources to produce a single view of the business.
Octopai
MAY 13, 2019
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.
Nutanix
OCTOBER 17, 2019
Nutanix introduced the first Hyperconverged platform to the market in 2011. While other Hyperconverged solutions have since come out, what differentiates Nutanix from the other solutions is the focus on implementing a highly scalable, reliable and performant distributed systems architecture
Jim Harris
MAY 5, 2017
Spelling, pronunciation, and examples of usage are included in the dictionary definition of a word, which is a good example of one of the many uses of metadata, namely to provide a definition, description, and context for data.
TDAN
SEPTEMBER 3, 2019
Organizations faced with the delivery of formal Data Governance or Information Governance programs recognize that there are several challenges they will face when getting started and as the program is operationalized. The challenges are not the same for all organizations.
Nutanix
SEPTEMBER 1, 2019
Nutanix introduced the first Hyperconverged platform to the market in 2011. While other Hyperconverged solutions have since come out, what differentiates Nutanix from the other solutions is the focus on implementing a highly scalable, reliable and performant distributed systems architecture
Nutanix
JULY 12, 2019
There’s no question that enterprise application usability has for the most part been left behind
erwin
JULY 17, 2019
Organizations need a real-time, accurate picture of the metadata landscape to: Discover data – Identify and interrogate metadata from various data management silos. Harvest data – Automate metadata collection from various data management silos and consolidate it into a single source.
erwin
MARCH 21, 2019
The lack of a central metadata repository is a far too common thorn in an organization’s side. A central metadata repository ensures an organization can acknowledge and get behind a single source of truth.
TDAN
AUGUST 6, 2019
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.
erwin
MAY 31, 2019
The typical notion is that enterprise architects and data (and metadata) architects are in opposite corners. With governance, which sets its fundamental components firmly on data, metadata and infrastructure. It’s time to consider data-driven enterprise architecture.
TDAN
OCTOBER 15, 2019
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.
TDAN
JULY 2, 2019
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.
TDAN
APRIL 30, 2019
Roles and responsibilities are the backbone of a successful information or data governance program.
erwin
JANUARY 24, 2019
In data governance terms, an automation framework refers to a metadata-driven universal code generator that works hand in hand with enterprise data mapping for: Pre-ETL enterprise data mapping. Governing metadata.
TDAN
APRIL 2, 2019
Enterprises today are focused on ensuring robust data governance, and are exploring different tools and approaches to support their efforts.
TDAN
APRIL 30, 2019
Data collection is getting more dispersed and voluminous every day. Corporate entities are constantly merging or splitting, and new lines of business are created in order to meet changing business challenges.
Perficient Data & Analytics
FEBRUARY 26, 2019
End-users are gaining more control of these assets, including the ability to integrate and manipulate them for their own purposes, and being able to select assets based on a relevance criteria not necessarily codified in classic metadata or semantic models.
TDAN
SEPTEMBER 17, 2019
There have been a couple of different things converged in my media feeds that highlight a key issue that all data management professionals and leaders in information management need to be conscious of – Group Think.
TDAN
AUGUST 20, 2019
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? The primary problem is the meaning of data within a certain context where it is used.
TDAN
APRIL 16, 2019
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 […].
TDAN
MARCH 19, 2019
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.
erwin
JULY 12, 2019
Activating their metadata to drive agile data preparation and governance through integrated data glossaries and dictionaries that associate policies to enable stakeholder data literacy.
TDAN
JULY 16, 2019
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.
TDAN
APRIL 2, 2019
If you are just starting out and feel overwhelmed by all the various definitions, explanations, and interpretations of data governance, don’t be alarmed. Even well-seasoned data governance veterans can struggle with the definition and explanation of what they do day to day.
TDAN
MAY 14, 2019
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.
TDAN
APRIL 2, 2019
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.
erwin
MARCH 14, 2019
BFSI, PHARMA, INSURANCE AND NON-PROFIT) CASE STUDIES FOR AUTOMATED METADATA-DRIVEN AUTOMATION. As stated above, a data governance platform that draws from a single metadata source is even more advantageous here.
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