Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. Remember that dark data is the data you have but don’t understand. So how do you find your dark data? Analyze your metadata.

IT 133

IT Metadata Data-driven Data Governance 133

IBM Big Data Hub

JANUARY 5, 2023

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story.

Metadata 52

Metadata Management Business Intelligence Data Governance 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? Answers will differ widely depending upon a business’ industry and strategy for growth.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

TDAN

APRIL 6, 2021

A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.

Data Warehouse 52

Data Warehouse Metadata Data-driven Modeling 52

Cloudera

JUNE 7, 2022

Only a fraction of data created is actually stored and managed, with analysts estimating it to be between 4 – 6 ZB in 2020. Clearly, hybrid data presents a massive opportunity and a tough challenge. Capitalizing on the potential requires the ability to harness the value of all of that data, no matter where it is.

IT 113

IT Data Architecture Unstructured Data Big Data 113

TDAN

NOVEMBER 2, 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? Answers will differ widely depending upon a business’ industry and growth strategy.

Data Governance 115

Data Governance Strategy Measurement IT 115

TDAN

MAY 31, 2022

The main goal of creating an enterprise data fabric is not new. It is the ability to deliver the right data at the right time, in the right shape, and to the right data consumer, irrespective of how and where it is stored. Data fabric is the common “net” that stitches integrated data from multiple data […].

Metadata 98

Metadata Enterprise IT Data Architecture 98

CIO Business Intelligence

JUNE 23, 2022

Only a fraction of data created is actually stored and managed, with analysts estimating it to be between 4 – 6 ZB in 2020. Clearly, hybrid data presents a massive opportunity and a tough challenge. Capitalizing on the potential requires the ability to harness the value of all of that data, no matter where it is.

IT 84

IT Data Architecture Unstructured Data Big Data 84

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data discoverability Unlike structured data, which is managed in well-defined rows and columns, unstructured data is stored as objects.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

erwin

JANUARY 17, 2020

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. What is Data Modeling?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

Ontotext

MAY 2, 2024

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. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

TDAN

JANUARY 5, 2021

In this age, data management has become a necessary routine. Organizations have started to uncover large sets of data in the form of Assets typically used for analysis and decision making. Understandably, Data Catalogs […].

Metadata 52

Metadata Management IT Data Governance 52

Cloudera

JUNE 7, 2023

The revised ZTMM is organized by five categories or pillars: identity, devices, networks, applications and workloads, and data, and four levels of maturity: traditional, initial, advanced, and optimal. The data is protected but it is also accessible by the people who need it. Understanding your data is critical to protecting the data.

Metadata 83

Metadata Data Lake Optimization Modeling 83

AWS Big Data

APRIL 26, 2023

Having an accurate and up-to-date inventory of all technical assets helps an organization ensure it can keep track of all its resources with metadata information such as their assigned oners, last updated date, used by whom, how frequently and more. This is a guest blog post co-written with Corey Johnson from Huron.

Metadata 52

Metadata Dashboards Visualization Consulting 52

Alation

APRIL 19, 2021

Data Cloud Migration Challenges and Solutions. Cloud migration is the process of moving enterprise data and infrastructure from on premise to off premise. This includes moving data, workloads, IT resources, and applications to the cloud. However, cloud data migration can be difficult. Alation & Global Data Strategy).

Cost-Benefit 111

Cost-Benefit Strategy Enterprise Data Strategy 111

Ontotext

SEPTEMBER 15, 2020

Data Fabric’ has reached where ‘Cloud Computing’ and ‘Grid Computing’ once trod. Data Fabric hit the Gartner top ten in 2019. This multiplicity of data leads to the growth silos, which in turns increases the cost of integration. Knowledge Graphs are the Warp and Weft of a Data Fabric.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

CIO Business Intelligence

DECEMBER 16, 2022

These included metadata design and development, quantitative analysis, regression analysis, continuous integration, data analytics, data strategy, identity and access management, machine learning, natural language processing, and more. Certifications, IT Skills.

Testing 93

Testing Metadata Data Processing Machine Learning 93

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. Data quality. For data to be trusted, it needs to be complete, accurate and well understood. Data silos.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

Cloudera

JANUARY 5, 2023

Data contains valuable insights for critical business decision-making, and the most innovative and successful organizations recognize data as a strategic resource that demands its own strategy. How this strategy looks depends on the organization’s unique business needs as one affects the other.

Cost-Benefit 52

Cost-Benefit Business Objectives Machine Learning Data Architecture 52

AWS Big Data

APRIL 19, 2023

This allows data consumers to easily identify new datasets and provides agility and innovation without spending hours doing analysis and research. Background The success of a data-driven organization recognizes data as a key enabler to increase and sustain innovation. It follows what is called a distributed system architecture.

Technology 78

Technology Data-driven Machine Learning Sales 78

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. One important aspect to a successful data strategy for any organization is data governance.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

TDAN

DECEMBER 3, 2019

I said I thought it affected all of them pretty profoundly, but perhaps the Metadata wedge the most. Recently, I was giving a presentation and someone asked me which segment of “the DAMA wheel” did I think semantics most affected. I thought I’d spend a bit of time to reflect on the question and answer […].

Metadata 88

Metadata Data Architecture IT Data Strategy 88

TDAN

DECEMBER 20, 2022

Over the past few months, my team in Castlebridge and I have been working with clients delivering training to business and IT teams on data management skills like data governance, data quality management, data modelling, and metadata management.

Metadata 52

Metadata Data Governance Data Quality Management 52

Sisense

MAY 28, 2020

This data flows into cloud-native warehouses where data teams manipulate it, allowing analysts to derive vital insights from it, and product teams embed those insights into products. Data is the bedrock on which the future of business is being built. Saving lives in real-time. Pressure on infrastructure builds.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. You need to process this to make it ready for analysis.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

AWS Big Data

APRIL 3, 2024

They recognize the importance of accurate, complete, and timely data in enabling informed decision-making and fostering trust in their analytics and reporting processes. Amazon DataZone data assets can be updated at varying frequencies. You can also update an existing data source to enable data quality.

Data Quality 85

Data Quality Visualization Metadata Metrics 85

CIO Business Intelligence

MARCH 21, 2022

Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies. Data scientist job description. Semi-structured data falls between the two.

Unstructured Data 136

Unstructured Data Data Analytics Analytics Structured Data 136

Octopai

JANUARY 31, 2021

Data lineage is an essential tool that among other benefits, can transform insights, help BI teams understand the root cause of an issue, as well as help achieve and maintain compliance. Through the use of data lineage, companies can better understand their data and its journey. Agile Data. A-Team Insight. Techcopedia.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

TDAN

SEPTEMBER 5, 2023

Data is the lifeblood of modern organizations, and as such, it must be carefully managed and protected. Whether it’s financial data, personal health information, or customer data, organizations that generate and manage data must implement a comprehensive data governance strategy.

Data Governance 52

Data Governance Business Intelligence Strategy Management 52

AWS Big Data

MAY 4, 2023

Over the last decade, we’ve seen a surge in data science frameworks coming to fruition, along with mass adoption by the data science community. Data scientists have access to the Jupyter notebook hosted on SageMaker. The OpenSearch Service domain stores metadata on the datasets connected at the Regions.

Data Processing 90

Data Processing Metadata Informatics Interactive 90

Cloudera

AUGUST 21, 2020

To find out more about how live-streaming data might impact the sector I sat down for a chat with Dinesh Chandrasekhar , Head of Product Marketing in Cloudera’s data-in-motion Business Unit. To start off, what are the advantages of a forward-looking data-in-motion strategy?

Enterprise 61

Enterprise Data Lake Strategy Metadata 61

CIO Business Intelligence

MARCH 29, 2022

The same principle applies to getting value from data. Organizations may acquire a lot of data, but they aren’t getting much value from it. It is estimated that nearly 75% of the data that enterprises collect remains unused, and thus, the value is not realized. What is data waste, and why does it happen?

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

TDAN

MAY 31, 2022

One very influential factor that can potentially undermine your data and document strategies is the natural and emotional reactions of people when things change. It is common to take great care in the selection and implementation of new technology.

Testing 52

Testing Interactive Strategy Software 52

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. Sharing data using LF-tags helps scale permissions and reduces the admin work for data lake builders.

Data Lake 78

Data Lake Data Governance Data Architecture Machine Learning 78