erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. What Is Metadata? Analyst firm Gartner defines metadata as “information that describes various facets of an information asset to improve its usability throughout its life cycle. It is metadata that turns information into an asset.”.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Cloudera

FEBRUARY 14, 2024

This blog discusses a few problems that you might encounter with Iceberg tables and offers strategies on how to optimize them in each of those scenarios. You can take advantage of a combination of the strategies provided and adapt them to your particular use cases. The rest of the blog will go into this in more detail.

Strategy 57

Strategy Optimization Snapshot Metadata 57

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

erwin

OCTOBER 24, 2019

While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. And to truly understand it , you need to be able to create and sustain an enterprise-wide view of and easy access to underlying metadata. This isn’t an easy task.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Ontotext

JANUARY 29, 2024

The generative AI buzz and interest in cloud migration shouldn’t be ignored, but as with any technology that requires data strategy, it’s critical that data and analytics professionals be crystal clear about their priorities and confident in the projects that will positively impact their business and goals.

Strategy 52

Strategy Management Metadata Data-driven 52

Alation

MARCH 14, 2023

Data gathering and use pervades almost every business function these days — and it’s widely acknowledged that businesses with a clear strategy around data are best placed to succeed in competitive, challenging markets such as defence. What is a data strategy? Why is a data strategy important?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

CDW Research Hub

JUNE 24, 2021

Metadata provides basic information (the who, what, when, where, why) about your data assets. Think of metadata as your data’s life story. By properly managing your metadata, you can improve data visibility, enhance any area of business that uses data and insights, and create opportunities for data reuse and sharing.

Metadata 52

Metadata Data Governance Management Strategy 52

erwin

JULY 17, 2019

Having a clearly defined digital transformation strategy is an essential best practice for successful digital transformation. But what makes a viable digital transformation strategy? Constructing A Digital Transformation Strategy: Data Enablement. Digital Transformation Strategy: Smarter Data.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

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. Metadata-Driven Automation in the Insurance Industry.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

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

Cloudera

APRIL 18, 2024

More Businesses Are Taking a Holistic Approach to Data Strategy One of the more common trends we saw coming up through conversations during the summit was the need for a reframing of how we approach data strategy—taking a much more holistic viewpoint to it than organizations otherwise would have in past years.

Analytics 108

Analytics Metadata Data Strategy Optimization 108

IBM Big Data Hub

JANUARY 5, 2023

Apply metadata to contextualize existing and new data to make it searchable and discoverable. Meaning, data architecture is a foundational element of your business strategy for higher data quality. A data strategy can help data architects create and implement a data architecture that improves data quality.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

IBM Big Data Hub

APRIL 10, 2023

The approach should be designed to provide enough metadata that key HR decision makers can identify which processes and decisions are informed by AI while maintaining anonymity and privacy in the data itself. The time for data professionals to meet this challenge is now.

Strategy 87

Strategy Data Architecture Cost-Benefit Reporting 87

Octopai

JANUARY 31, 2021

Incorporating data lineage into an organization’s strategy can make a huge difference when it comes to making accurate business decisions and having a handle on the information they already possess. Our list of Top 10 Data Lineage Podcasts, Blogs, and Websites To Follow in 2021. Data Engineering Podcast. Agile Data. Techcopedia.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

Alation

MARCH 1, 2023

To learn the answer, we sat down with Karla Kirton , Data Architect at Blockdaemon, a blockchain company, to discuss data strategy , decentralization, and how implementing Alation has supported them. What is your data strategy and how did you begin to implement it? Here’s a recap of our discussion.

Data Strategy 52

Data Strategy Strategy Metadata Interactive 52

Alation

DECEMBER 15, 2021

An effective data governance strategy is critical for unlocking the full benefits of this information. Let’s explore the key steps for building an effective data governance strategy. What is a Data Governance Strategy? A data governance strategy provides a framework that connects people to processes and technology.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Alation

OCTOBER 5, 2021

Answers will differ widely depending upon a business’ industry and strategy for growth. The first step towards a successful data governance strategy is setting appropriate goals and milestones. Yet, so many companies today are still failing miserably in implementing data strategy and governance protocols.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

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

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

AWS Big Data

OCTOBER 3, 2023

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. In this method, the metadata are recreated in an isolated environment and colocated with the existing data files. This method shadows the source dataset in batches.

Data Lake 104

Data Lake Metadata Snapshot Recreation/Entertainment 104

IBM Big Data Hub

MAY 20, 2024

Machine learning (ML) has become a critical component of many organizations’ digital transformation strategy. In this blog post, we will explore the importance of lineage transparency for machine learning data sets and how it can help establish and ensure, trust and reliability in ML conclusions.

Machine Learning 89

Machine Learning Modeling Strategy Digital Transformation 89

IBM Big Data Hub

JUNE 30, 2022

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. Learn more about how to design and implement a data strategy that takes advantage of a hybrid multicloud landscape.

Data Strategy 56

Data Strategy Strategy Business Objectives Data-driven 56

Alation

MAY 10, 2021

In other words, they have a system in place for a data-driven strategy. The catalog gathers metadata, (or data about data), to add context to every asset. In phase one, an enterprise must create a data strategy , which will inform later plans. With a strategy in place, the next two phases are preparation and implementation.

Strategy 80

Strategy Enterprise Data Strategy Data Governance 80

Cloudera

MAY 6, 2021

In this article, I will be focusing on the contribution that a multi-cloud strategy has towards these value drivers, and address a question that I regularly get from clients: Is there a quantifiable benefit to a multi-cloud deployment? Risk Mitigation. Business Value Acceleration.

Strategy 91

Strategy Cost-Benefit Optimization Risk 91

IBM Big Data Hub

OCTOBER 4, 2023

It’s no longer a nice-to-have, but an integral part of a successful data strategy. Also, a lakehouse can introduce definitional metadata to ensure clarity and consistency, which enables more trustworthy, governed data. The first step for successful AI is access to trusted, governed data to fuel and scale the AI.

Data Lake 79

Data Lake Metadata Cost-Benefit Data Warehouse 79

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Apache Iceberg addresses customer needs by capturing rich metadata information about the dataset at the time the individual data files are created.

Data Lake 120

Data Lake Data Processing Metadata Snapshot 120

Timo Elliott

JANUARY 6, 2022

In a previous blog , I explored the value of dark data and how it can reveal insights that can streamline processes, improve customer experiences, generate more revenue – and maybe even help make the world a better place. Analyze your metadata. The data you’ve collected and saved over the years isn’t free. Use people.

IT 133

IT Metadata Data-driven Data Governance 133

Cloudera

JULY 13, 2023

In this blog, we will discuss performance improvement that Cloudera has contributed to the Apache Iceberg project in regards to Iceberg metadata reads, and we’ll showcase the performance benefit using Apache Impala as the query engine. The data files and metadata files in Iceberg format are immutable.

Metadata 70

Metadata Snapshot Data Warehouse Statistics 70

AWS Big Data

MAY 28, 2024

Integration with the AWS Glue Data Catalog as a metadata store for Flink applications The AWS Glue Data Catalog is a centralized metadata repository for data assets across various data sources, and provides a unified interface to store and query information about data formats, schemas, and sources.

Data Processing 84

Data Processing Cost-Benefit Metadata Optimization 84

Cloudera

APRIL 9, 2019

A hybrid, multi-cloud strategy is the best approach to managing these distributed, heterogeneous data ecosystems. Three key reasons why a hybrid, multi-cloud strategy is important for your organization: Data gravity. Transforming Your Business with Multi-cloud and Hybrid Strategies. appeared first on Cloudera Blog.

Strategy 53

Strategy Experimentation Metadata Business Objectives 53

erwin

JUNE 26, 2020

If you’re serious about a data-driven strategy , you’re going to need a data catalog. Organizations with particularly deep data stores might need a data catalog with advanced capabilities, such as automated metadata harvesting to speed up the data preparation process. Three Types of Metadata in a Data Catalog.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

erwin

OCTOBER 8, 2020

With all these diverse metadata sources, it is difficult to understand the complicated web they form much less get a simple visual flow of data lineage and impact analysis. The metadata-driven suite automatically finds, models, ingests, catalogs and governs cloud data assets. Subscribe to the erwin Expert Blog.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

erwin

MAY 31, 2019

The traditional approach to enterprise architecture – the analysis, design, planning and implementation of IT capabilities for the successful execution of enterprise strategy – seems to be missing something … data. When it comes to technology and governance strategies , policies and standards, data should be at the center.

Data-driven 104

Data-driven Enterprise Metadata Strategy 104

IBM Big Data Hub

SEPTEMBER 12, 2022

Build a foundation using a common catalog and metadata. Similarly, active metadata — data about data — is at the heart of how a data fabric delivers on privacy for the same reason as a common data catalog. Once metadata has been created, it can be tagged, signifying which data is sensitive, limiting who has access to it and so forth.

Metadata 93

Metadata Data Governance Enterprise Data Architecture 93

CIO Business Intelligence

DECEMBER 13, 2023

and applying and enriching metadata helps organizations take a big step toward innovating with generative AI. User-generated content , such as blogs, forums, and customer feedback, to understand customer preferences, improve product recommendations, and tailor user experiences. Artificial Intelligence

Unstructured Data 95

Unstructured Data IoT Metadata Manufacturing 95

AWS Big Data

MAY 24, 2023

You can adjust your retry strategy by increasing the maximum retry limit for the default exponential backoff retry strategy or enabling and configuring the additive-increase/multiplicative-decrease (AIMD) retry strategy. You still need to set appropriate EMRFS retries to provide additional resiliency.

Data Lake 87

Data Lake Snapshot Metadata Optimization 87

Cloudera

NOVEMBER 13, 2020

This is part of our series of blog posts on recent enhancements to Impala. The commonly-accepted best practice in database system design for years is to use an exhaustive search strategy to consider all the possible variations of specific database operations in a query plan. Metadata Caching. More on this below.

Optimization 143

Optimization Metadata Statistics Cost-Benefit 143