Astera

MARCH 28, 2024

The former offers a comprehensive view of an organization’s data assets. It facilitates data discovery and exploration by enabling users to easily search and explore available data assets. This functionality includes data definitions, schema details, data lineage, and usage statistics.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Data Pine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 144

Business Intelligence Business Intelligence Artificial Intelligence Data Discovery 144

Astera

APRIL 4, 2024

Data governance’s primary purpose is to ensure organizational data assets’ quality, integrity, security, and effective use. The key objectives of Data Governance include: Enhancing Clear Ownership: Assigning roles to ensure accountability and effective management of data assets.

Data Governance 52

Data Governance Government E-Commerce Data Quality 52

Astera

FEBRUARY 28, 2024

Data Governance and Documentation Establishing and enforcing rules, policies, and standards for your data warehouse is the backbone of effective data governance and documentation. Keeping track of metadata can help you understand the data, facilitate data integration , enable data lineage tracing, and enhance data quality.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

APRIL 28, 2023

For example, GE Healthcare leverage AI-powered data cleansing tools to improve the quality of data in its electronic medical records, reducing the risk of errors in patient diagnosis and treatment. Continuous Data Quality Monitoring According to Gartner , poor data quality cost enterprises an average of $15 million per year.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Astera

APRIL 24, 2024

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

Data Governance 52

Data Governance Government Data Architecture Data Quality 52

Astera

FEBRUARY 27, 2024

It also supports predictive and prescriptive analytics, forecasting future outcomes and recommending optimal actions based on data insights. Enhancing Data Quality A data warehouse ensures high data quality by employing techniques such as data cleansing, validation, integration, and standardization during the ETL process.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

JANUARY 12, 2024

Self-Serve Data Infrastructure as a Platform: A shared data infrastructure empowers users to independently discover, access, and process data, reducing reliance on data engineering teams. However, governance remains essential in a Data Mesh approach to ensure data quality and compliance with organizational standards.

Data Architecture 52

Data Architecture Data Warehouse Data Quality Government 52

Astera

MARCH 20, 2024

Enterprise data management (EDM) is a holistic approach to inventorying, handling, and governing your organization’s data across its entire lifecycle to drive decision-making and achieve business goals. It provides a strategic framework to manage enterprise data with the highest standards of data quality , security, and accessibility.

Data Management 52

Data Management Master Data Management Government Data Warehouse 52

Astera

MAY 8, 2024

Improved Data Quality and Governance: Access to high-quality data is crucial for making informed business decisions. A business glossary is critical in ensuring data integrity by clearly defining data collection, storage, and analysis terms.

Data Governance 52

Data Governance Government Healthcare Retail 52

Sisense

APRIL 15, 2021

Your company is gathering data (and has likely been doing so for years), and you’ve probably got a system or two to glean insights from that data to make smarter decisions. Why shouldn’t business members in all strata participate in building and deploying new data models to power their analytics needs?

Artificial Intelligence 98

Artificial Intelligence Data Modelling Cloud Computing Data Discovery 98

Astera

MAY 14, 2024

This metadata variation ensures proper data interpretation by software programs. Process metadata: tracks data handling steps. It ensures data quality and reproducibility by documenting how the data was derived and transformed, including its origin.

Government 52

Government Data Governance Master Data Management Documentation 52

The BAWorld

NOVEMBER 28, 2021

Excel has various features and functions which make it a powerful data analysis tool. If you want to learn more about exploratory data analysis, check out the new blog on Exploratory Data Analysis Tools , which outlines the steps in your data science journey. Core Data Wrangling Activities. Discovering.

Visualization 52

Visualization Data Visualization Data Discovery Data Quality 52

Data Pine

DECEMBER 4, 2019

This data analytics buzzword is somehow a déjà-vu. Augmented analytics was indeed previously referred to as “Smart Data Discovery”. It is the combination of several data processes that, instead of just giving back data, but provides a valuable, strategy-changing recommendation. Augmented Analytics. Graph Analytics.

Business Intelligence 84

Business Intelligence Business Intelligence IBM Support IBM Maintenance 84

Dataversity

NOVEMBER 27, 2023

However, making the right data available to the right people at the right time is becoming more and more challenging. While the ability to perform analytics on huge volumes of data is beefing up […] The post 7 Data Democratization Trends to Watch appeared first on DATAVERSITY.

Data Governance 173

Data Governance Data Discovery Data Quality Data Security 173

Astera

MAY 30, 2024

Variety : Data comes in all formats – from structured, numeric data in traditional databases to emails, unstructured text documents, videos, audio, financial transactions, and stock ticker data. Veracity: The uncertainty and reliability of data. Veracity addresses the trustworthiness and integrity of the data.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

Data Pine

MAY 31, 2022

Since we live in a digital age, where data discovery and big data simply surpass the traditional storage and manual implementation and manipulation of business information, companies are searching for the best possible solution for handling data. It is evident that the cloud is expanding. It’s completely free!

Cloud Computing 95

Cloud Computing Cybersecurity Government Business Intelligence 95

Dataversity

MARCH 21, 2022

While data lakes and data warehouses are both important Data Management tools, they serve very different purposes. If you’re trying to determine whether you need a data lake, a data warehouse, or possibly even both, you’ll want to understand the functionality of each tool and their differences.

Data Warehouse 246

Data Warehouse Data Management Data Governance Data Discovery 246

Data Pine

SEPTEMBER 27, 2022

You can also utilize data discovery tools to get additional insight into the importance of data and how to approach it. Getting your hands on genuine data that you can relate to is the most effective way to learn, and these best books on SQL will offer you the guidance you need for true practical success.

IBM cost 117

IBM cost Data Warehouse Business Intelligence Business Intelligence 117

Dataversity

SEPTEMBER 20, 2021

Click to learn more about author Balaji Ganesan. Sources indicate 40% more Americans will travel in 2021 than those in 2020, meaning travel companies will collect an enormous amount of personally identifiable information (PII) from passengers engaging in “revenge” travel.

Digital 246

Digital Data Governance Data Discovery Data Quality 246

Dataversity

JUNE 13, 2022

When data is not viable for integration across systems and processes, business users will seldom have the right coverage of data. If people lack knowledge about data and its importance logically, it often becomes a challenge, which leads to less impactful decisions.

Data Governance 130

Data Governance Data Discovery Data Quality Data Architecture 130

Dataversity

FEBRUARY 9, 2022

“Data Governance” is such an interesting term. As data started becoming more critical to business in the last few years, this idea was introduced to define the business processes necessary to comply with regulatory requirements.

Data Governance 130

Data Governance Government Data Discovery Data Quality 130

Dataversity

FEBRUARY 19, 2021

Enterprises are modernizing their data platforms and associated tool-sets to serve the fast needs of data practitioners, including data scientists, data analysts, business intelligence and reporting analysts, and self-service-embracing business and technology personnel. Click to learn more about author Tejasvi Addagada.

Business Intelligence 147

Business Intelligence Business Intelligence Data Modelling Data Governance 147

Dataversity

AUGUST 2, 2021

Enterprise organizations evaluate several factors when choosing a data migration vendor. The post Discovery and Reporting: The Bread and Butter of Data Migration appeared first on DATAVERSITY. Click to learn more about author Daniel Esposito.

Data Discovery 130

Data Discovery Data Governance Data Quality Government 130

Dataversity

APRIL 7, 2021

It’s time-consuming – and often very costly – for enterprises to perform a network-attached storage (NAS) or object data migration. As moving unstructured data has proliferated over the past decade, with as much as 90% of all data defined as unstructured data, the task has become increasingly […].

Data Governance 130

Data Governance Data Discovery Data Quality Government 130