Cloudera

APRIL 18, 2024

In those discussions, it was clear that everyone understood the need to treat data estates more cohesively as a whole—that means bringing more attention to security, data governance, and metadata management, the latter of which has become increasingly popular. Learn more about how Cloudera is accelerating enterprise AI.

Analytics 105

Analytics Metadata Data Strategy Optimization 105

erwin

DECEMBER 12, 2019

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 in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

CIO Business Intelligence

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Octopai

FEBRUARY 12, 2020

Like any good puzzle, metadata management comes with a lot of complex variables. That’s why you need to use data dictionary tools, which can help organize your metadata into an archive that can be navigated with ease and from which you can derive good information to power informed decision-making. Download Now.

Metadata 54

Metadata Enterprise Management Data Warehouse 54

Octopai

SEPTEMBER 14, 2020

Modern data processing depends on metadata management to power enhanced business intelligence. Metadata is of course the information about the data, and the process of managing it is mysterious to those not trained in advanced BI. In this article, you will learn: What does metadata management do? What is metadata management?

Metadata 52

Metadata Management Data Processing Machine Learning 52

Ontotext

AUGUST 19, 2020

Metadata used to be a secret shared between system programmers and the data. Metadata described the data in terms of cardinality, data types such as strings vs integers, and primary or foreign key relationships. Inevitably, the information that could and needed to be expressed by metadata increased in complexity.

Metadata 59

Metadata Knowledge Discovery Cost-Benefit Data Governance 59

erwin

NOVEMBER 6, 2019

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.”. The post Metadata Management, Data Governance and Automation appeared first on erwin, Inc.

Metadata 102

Metadata Data Governance Management Cost-Benefit 102

Octopai

DECEMBER 22, 2019

As 2019 comes to a close, we think it’s the perfect time to review trends in metadata management as well as look at some of Octopai’s own highlights. Metadata is everywhere and its success depends on deploying the right resources for its management. Named by Solutions Review as an Analytics Vendor to Watch, 2020.

Metadata 54

Metadata Management OLAP Data Governance 54

erwin

DECEMBER 12, 2019

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 in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Ontotext

FEBRUARY 1, 2024

Knowledge graphs The final step in model complexity covered in my talk is the advent of enterprise knowledge graphs, and, more specifically, what Synaptica calls content-aware knowledge graphs. Extreme scale Many, if not most, enterprise taxonomies have under 10,000 concepts. What do we mean by content aware knowledge graphs?

Enterprise 59

Enterprise Management Metadata Modeling 59

erwin

NOVEMBER 13, 2020

The business challenges facing organizations today emphasize the value of enterprise architecture (EA) , so the future of EA is closer than you think. See also: What Is Enterprise Architecture? . Let’s dig into the first two and then look at the role of enterprise architects and how to ensure your EA tools are up to the tasks ahead.

Enterprise 131

Enterprise Digital Transformation Key Performance Indicator Data-driven 131

Smarten

JANUARY 30, 2024

Business users cannot even hope to prepare data for analytics – at least not without the right tools. Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation? It’s simple.

Analytics 67

Analytics Data Quality Visualization Metadata 67

Cloudera

MARCH 3, 2022

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance. In 2019, the U.K.’s

Data Governance 96

Data Governance Enterprise Data Quality Metadata 96

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. Donna Burbank. IRM UK Connects.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

AWS Big Data

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. This is critical for fast-moving enterprises to augment data structures to support new use cases.

Snapshot 111

Snapshot Data Lake Metadata Recreation/Entertainment 111

Alation

AUGUST 18, 2022

I’m convinced that a fundamental shift in approach to lineage is needed to drive both the value of data (and the analytics culture) to a new level of effectiveness. The complex challenge here is to have the lineage be intelligently updated as the data landscape and processing dynamically bubbles and changes daily across an enterprise.

Metadata 69

Metadata Visualization Statistics Data Architecture 69

Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses.”.

Metadata 52

Metadata Management Data Lake Data Governance 52

AWS Big Data

FEBRUARY 29, 2024

Working with large language models (LLMs) for enterprise use cases requires the implementation of quality and privacy considerations to drive responsible AI. However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

AWS Big Data

APRIL 3, 2024

For many enterprises and large organizations, it is not feasible to have one processing engine or tool to deal with the various business requirements. Customers are using AWS and Snowflake to develop purpose-built data architectures that provide the performance required for modern analytics and artificial intelligence (AI) use cases.

Data Lake 94

Data Lake Snapshot Metadata Data Architecture 94

AWS Big Data

NOVEMBER 16, 2023

This post discusses the most pressing needs when designing an enterprise-grade Data Vault and how those needs are addressed by Amazon Redshift in particular and AWS cloud in general. The first post in this two-part series discusses best practices for designing enterprise-grade data vaults of varying scale using Amazon Redshift.

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

Cloudera

AUGUST 3, 2021

Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Improve Visibility within Supply Chains.

Analytics 108

Analytics Digital Transformation Risk Forecasting 108

Ontotext

APRIL 10, 2024

This is a “ Datastrophe “ Data managed correctly can turn assets into actionable insights, left unmanaged it can be the uranium, causing massive damage to enterprises with data and security breaches being rampant. Proliferation of data catalogs across vendors creates metadata silos and does little to connect the data semantically.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Alation

MAY 19, 2022

Alation attended last week’s Gartner Data and Analytics Summit in London from May 9 – 11, 2022. Gartner Data & Analytics Summit 2022: Keynote Highlights. Active metadata gives you crucial context around what data you have and how to use it wisely. These are three areas in which analytics is rapidly advancing.

Metadata 52

Metadata Data Analytics Analytics Data Governance 52

AWS Big Data

MARCH 7, 2024

You can take all your data from various silos, aggregate that data in your data lake, and perform analytics and machine learning (ML) directly on top of that data. You can now analyze infrequently queried data in cloud object stores and simultaneously use the operational analytics and visualization capabilities of OpenSearch Service.

Data Lake 112

Data Lake Analytics Dashboards Metrics 112

Ontotext

JULY 13, 2023

For example, offering more of the same product or content instead of complementary items Analytics tools that don’t really support decision making Chatbots that fail the Alan Turing test You name it! How can you build knowledge graphs for enterprise applications? Enterprises generate an enormous amount of data and content every minute.

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

AWS Big Data

APRIL 16, 2024

Running Apache Airflow at scale puts proportionally greater load on the Airflow metadata database, sometimes leading to CPU and memory issues on the underlying Amazon Relational Database Service (Amazon RDS) cluster. A resource-starved metadata database may lead to dropped connections from your workers, failing tasks prematurely.

Metadata 95

Metadata Metrics Testing Management 95

Alation

FEBRUARY 12, 2020

Gone are the days when static metadata repositories and manual curation were enough (if they ever really were). In a recent report*, Gartner analysts, Ehtisham Zaidi and Guido De Simoni, call augmented data catalogs an “enterprise must-have” for data and analytics leaders. Hundreds (even thousands) of data consumers.

Enterprise 52

Enterprise Metadata Machine Learning Reporting 52

Alation

MARCH 31, 2023

I’m talking about not just Walt Disney World, but also this year’s Gartner Data & Analytics Summit , which took place last month in Orlando at the landmark resort. The active metadata helix Indeed, automation was on everyone’s minds. It’s the place where dreams come true. We couldn’t agree more.

Data Analytics 52

Data Analytics Analytics Metadata Data Governance 52

AWS Big Data

DECEMBER 13, 2023

For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users. EDLS job steps and metadata Every EDLS job comprises one or more job steps chained together and run in a predefined order orchestrated by the custom ETL framework.

Metadata 87

Metadata Data Lake Visualization Data Transformation 87

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. The following diagram is a conceptual analytics data hub reference architecture. This reference architecture partly combines a data hub and data lake to enable comprehensive analytics services.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

Alation

DECEMBER 11, 2019

Gone are the days when static metadata repositories and manual curation were enough (if they ever really were). To keep up with the rapid influx of data, the many disparate data environments, and the rise in self-service analytics users, enterprises need an […]. Millions of datasets.

Enterprise 52

Enterprise Metadata Analytics Machine Learning 52

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. Get these wrong and chances are your enterprise processes and systems will suffer.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

AWS Big Data

JULY 27, 2023

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.

Data Warehouse 81

Data Warehouse Analytics Metadata Dashboards 81

Ontotext

MAY 2, 2024

Particularly those on the “the create side of the house” who are tasked to deliver insights and analytics. Such inconsistencies bring lowered trust in the outcomes analytics and insights leaders try to get. Another challenge is the data models that represent how insights and analytics teams see the world.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

IBM Big Data Hub

JUNE 8, 2022

By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage. AI and Analytics is only good as the quality of data been used for it. Furthermore, to help the framework scale across the enterprise, it needs to be automated. Data silos.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

AWS Big Data

MARCH 13, 2024

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. The Data Catalog provides metadata that allows analytics applications using Athena to find, read, and process the location data stored in Amazon S3. Choose Run.

Analytics 94

Analytics IoT Metadata Internet of Things 94

AWS Big Data

OCTOBER 3, 2023

You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. Analytics use cases on data lakes are always evolving. In this method, the metadata are recreated in an isolated environment and colocated with the existing data files.

Data Lake 102

Data Lake Metadata Snapshot Recreation/Entertainment 102