CIO Business Intelligence

NOVEMBER 19, 2024

The next phase of this transformation requires an intelligent data infrastructure that can bring AI closer to enterprise data. The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows.

Management 116

Management Unstructured Data Deep Learning Metadata 116

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. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

erwin

NOVEMBER 6, 2019

In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. And this time, you guessed it – we’re focusing on data automation and how it could impact metadata management and data governance.

Metadata 102

Metadata Data Governance Management Cost-Benefit 102

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

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

Ontotext

JULY 29, 2021

The Semantic Web, both as a research field and a technology stack, is seeing mainstream industry interest, especially with the knowledge graph concept emerging as a pillar for data well and efficiently managed. And what are the commercial implications of semantic technologies for enterprise data? What is it? Which Semantic Web?

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Octopai

JANUARY 31, 2022

If you’re a mystery lover, I’m sure you’ve read that classic tale: Sherlock Holmes and the Case of the Deceptive Data, and you know how a metadata catalog was a key plot element. In The Case of the Deceptive Data, Holmes is approached by B.I. He goes on to explain: Reasons for inaccurate data. Big data is BIG.

Metadata 97

Metadata IT Unstructured Data IoT 97

AWS Big Data

DECEMBER 17, 2024

Industry-leading price-performance Amazon Redshift offers up to three times better price-performance than alternative cloud data warehouses. Amazon Redshift scales linearly with the number of users and volume of data, making it an ideal solution for both growing businesses and enterprises.

Data Lake 98

Data Lake Data Warehouse Data-driven Optimization 98

erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. CCPA vs. GDPR: Key Differences.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. Metadata management is the key to managing and governing your data and drawing intelligence from it. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Enterprise Modeling Management 93

erwin

OCTOBER 8, 2020

By using automated and repeatable capabilities, you can quickly and safely migrate data to the cloud and govern it along the way. But transforming and migrating enterprise data to the cloud is only half the story – once there, it needs to be governed for completeness and compliance. GDPR, CCPA, HIPAA, SOX, PIC DSS).

Data Governance 145

Data Governance Metadata Testing Data Lake 145

AWS Big Data

DECEMBER 4, 2024

This unified catalog enables engineers, data scientists, and analysts to securely discover and access approved data and models using semantic search with generative AI-created metadata. Having confidence in your data is key. And move with confidence and trust with built-in governance to address enterprise security needs.

Data Analytics 104

Data Analytics Analytics Data Lake Data Quality 104

CIO Business Intelligence

MARCH 24, 2023

Whereas data governance is about the roles, responsibilities, and processes for ensuring accountability for and ownership of data assets, DAMA defines data management as “an overarching term that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

erwin

JANUARY 30, 2020

Digital transformation and data standards/uniformity round out the top five data governance drivers, with 37 and 36 percent, respectively. Constructing a Digital Transformation Strategy: How Data Drives Digital. However, more than 50 percent say they have deployed metadata management, data analytics, and data quality solutions.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

AWS Big Data

APRIL 3, 2024

Businesses are constantly evolving, and data leaders are challenged every day to meet new requirements. For many enterprises and large organizations, it is not feasible to have one processing engine or tool to deal with the various business requirements. This post is co-written with Andries Engelbrecht and Scott Teal from Snowflake.

Data Lake 127

Data Lake Snapshot Metadata Data Architecture 127

erwin

DECEMBER 9, 2024

And if it isnt changing, its likely not being used within our organizations, so why would we use stagnant data to facilitate our use of AI? The key is understanding not IF, but HOW, our data fluctuates, and data observability can help us do just that.

Metadata 52

Metadata Data Quality Sales Modeling 52

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

David Menninger's Analyst Perspectives

OCTOBER 24, 2024

Data fabric refers to technology products that can be used to integrate, manage and govern data across distributed environments, supporting the cultural and organizational data ownership and access goals of data mesh.

Management 130

Management Data-driven Data Governance Data Lake 130

erwin

MAY 27, 2020

Visualizing data from anywhere defined by its context and definition in a central model repository, as well as the rules for governing the use of those data elements, unifies enterprise data management. A single source of data truth helps companies begin to leverage data as a strategic asset.

Modeling 98

Modeling Metadata Data Governance Visualization 98

CIO Business Intelligence

JULY 18, 2024

Technologies such as AI, cloud computing, and the Internet of Things (IoT), require the right infrastructure to support moving data securely across environments. IT teams need to capture metadata to know where their data comes from, allowing them to map out its lineage and flow. These issues add up and lead to unreliability.

Management 111

Management Internet of Things IoT Metadata 111

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 governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 124

Data Governance Unstructured Data Metadata Data Lake 124

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 111

Metadata Data Lake Visualization Data Quality 111

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. SQL or NoSQL?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

IBM Big Data Hub

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

Cloudera

JUNE 25, 2019

Cloudera Unveils Industry’s First Enterprise Data Cloud in Webinar. On June 18th, Cloudera provided an exclusive preview of these capabilities, and more, with the introduction of Cloudera Data Platform (CDP), the industry’s first enterprise data cloud. Cloudera Data Platform. An enterprise data cloud is: .

Enterprise 87

Enterprise Machine Learning Recreation/Entertainment IoT 87

IBM Big Data Hub

MARCH 25, 2022

A data fabric is an architectural approach that enables organizations to simplify data access and data governance across a hybrid multicloud landscape for better 360-degree views of the customer and enhanced MLOps and trustworthy AI. The post What is a data fabric architecture?

Metadata 104

Metadata Data Quality Data Governance Data Integration 104

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. In-place data upgrade In an in-place data migration strategy, existing datasets are upgraded to Apache Iceberg format without first reprocessing or restating existing data.

Data Lake 122

Data Lake Metadata Snapshot Recreation/Entertainment 122

AWS Big Data

JUNE 10, 2024

Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. The open table format accelerates companies’ adoption of a modern data strategy because it allows them to use various tools on top of a single copy of the data.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

Octopai

OCTOBER 23, 2019

The same is true of enterprise data. Modern enterprises find themselves sitting on mountains of data. There’s value locked in that data—knowledge that can drive innovation, market insights, and strategic plans. But much of the data is separated, residing in incompatible silos. Why Go To All This Trouble?

Enterprise 63

Enterprise IT Metadata Machine Learning 63

Ontotext

JANUARY 10, 2024

The reason is that the inherent complexity of big enterprises is such that this is the simplest model that enables them to “connect the dots” across the different operational IT systems and turn the diversity of their business into a competitive advantage. This requires new tools and new systems, which results in diverse and siloed data.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Data Warehouse 121

Data Warehouse Metadata Data Integration Business Intelligence 121

AWS Big Data

SEPTEMBER 7, 2023

We will partition and format the server access logs with Amazon Web Services (AWS) Glue , a serverless data integration service, to generate a catalog for access logs and create dashboards for insights. Both the user data and logs buckets must be in the same AWS Region and owned by the same account. Big Data Architect.

Metadata 116

Metadata Dashboards Metrics Visualization 116

AWS Big Data

FEBRUARY 26, 2025

S3 Tables integration with the AWS Glue Data Catalog is in preview, allowing you to stream, query, and visualize dataincluding Amazon S3 Metadata tablesusing AWS analytics services such as Amazon Data Firehose , Amazon Athena , Amazon Redshift, Amazon EMR, and Amazon QuickSight. With AWS Glue 5.0, With AWS Glue 5.0,

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

Ontotext

JANUARY 25, 2024

In the current data management landscape, enterprises have to deal with diverse and dispersed data at unimaginable volumes. Among this complexity of siloed data and content, valuable business insights and opportunities get lost. This is a core component of most data fabric based implementations.

Enterprise 64

Enterprise Management Cost-Benefit Metadata 64

Ontotext

JULY 12, 2024

Graph technologies are essential for managing and enriching data and content in modern enterprises. But to develop a robust data and content infrastructure, it’s important to partner with the right vendors. As a result, enterprises can fully unlock the potential hidden knowledge that they already have.

Enterprise 59

Enterprise Cost-Benefit Metadata Data Integration 59

erwin

JANUARY 24, 2019

In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way. Governing metadata.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71