erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

IBM Big Data Hub

AUGUST 15, 2022

How does a data architecture impact your ability to build, scale and govern AI models? To be a responsible data scientist, there’s two key considerations when building a model pipeline: Bias: a model which makes predictions for people of different group (or race, gender ethnic group etc.)

Data mining 60

Data mining Risk Modeling Risk Management 60

IBM Big Data Hub

JUNE 30, 2022

The diversity of data types, data processing, integration and consumption patterns used by organizations has grown exponentially. Extend data governance to foster trust in your data by creating transparency, eliminating bias and ensuring explainability for data and insights fueled by machine learning and AI.

Data Strategy 56

Data Strategy Strategy Business Objectives Data-driven 56

erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Sisense

SEPTEMBER 3, 2020

We live in a constantly-evolving world of data. That means that jobs in data big data and data analytics abound. The wide variety of data titles can be dizzying and confusing! Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Why telco should consider modern data architecture. The challenges.

Data Architecture 86

Data Architecture Cost-Benefit Digital Transformation Business Driver 86

IBM Big Data Hub

SEPTEMBER 7, 2022

Do your data governance systems desperately need an overhaul or is your data visualization in need of a spruce up? Do you accept that data science takes a slight back seat while you improve the data quality? The post A steadfast community in an ever-changing data landscape appeared first on Journey to AI Blog.

Data Strategy 52

Data Strategy Strategy Data-driven Data Quality 52

TDAN

SEPTEMBER 7, 2022

Insightful and accurate data is the lifeblood of any successful business. There are many ways to ensure high-quality information in Salesforce Sales Cloud with regular cleansing routines that keep up-to date records for each […].

Sales 52

Sales Data Quality Data Architecture IT 52

IBM Big Data Hub

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. Organizations can harness the full potential of their data while reducing risk and lowering costs. However, businesses scaling AI face entry barriers.

Cost-Benefit 68

Cost-Benefit Data Integration Data Architecture Manufacturing 68

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. 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. Addressing the Complexities of Metadata Management.

Metadata 104

Metadata Management Data-driven Data Architecture 104

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 80

Management Metadata Data Architecture Data Lake 80

IBM Big Data Hub

AUGUST 1, 2022

Bad data costs companies an average of $15 million. . 73% of business executives are unhappy with their data quality. . 61% of organizations are unable to harness data to create a sustained competitive advantage. . Thus, why we have made efforts to help companies improve their business practices through data analysis.

Unstructured Data 52

Unstructured Data Deep Learning Data Quality Data Architecture 52

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web. Linked Data and Volume.

Cost-Benefit 87

Cost-Benefit Technology Big Data Metadata 87

IBM Big Data Hub

DECEMBER 4, 2023

During configuration, an organization constructs its data architecture and defines user roles. Specifically, to ensure the accuracy of data, organizations should test the following variables: Data archive: Make sure older data that might not have been imported to Oracle is archived securely and is easy to access.

Testing 73

Testing Consulting Digital Transformation Cost-Benefit 73

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. Spoiler alert!

Metadata 52

Metadata IT Metrics Data-driven 52

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web. Linked Data and Volume.

Cost-Benefit 75

Cost-Benefit Technology Big Data Metadata 75

IBM Big Data Hub

JANUARY 17, 2023

As part of a data fabric, IBM’s data integration capability creates a roadmap that helps organizations connect data from disparate data sources, build data pipelines, remediate data issues, enrich data quality, and deliver integrated data to multicloud platforms.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. This results in more marketable AI-driven products and greater accountability.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59