Astera

JUNE 14, 2024

Unlike passive approaches, which might only react to issues as they arise, active data governance anticipates and mitigates problems before they impact the organization. Here’s a breakdown of its key components: Data Quality: Ensuring that data is complete and reliable.

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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.

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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.

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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

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Astera

SEPTEMBER 4, 2024

Unified data governance Even with decentralized data ownership, the data mesh approach emphasizes the need for federated data governance , helping you implement shared standards, policies, and protocols across all your decentralized data domains.

Data Architecture 52

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Astera

JUNE 4, 2024

This feature is valuable for understanding data dependencies and ensuring data quality across the entire data lifecycle. While data dictionaries offer some lineage information for specific fields within a database, data catalogs provide a more comprehensive lineage view across various data sources.

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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.

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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.

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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.

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Astera

JULY 12, 2024

This catalog serves as a comprehensive inventory, documenting the metadata, location, accessibility, and usage guidelines of data resources. The primary purpose of a resource catalog is to facilitate efficient data discovery, governance , and utilization.

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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.

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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!

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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.

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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.

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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.

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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.

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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.

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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.

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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 […].

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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

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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

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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

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Data Pine

MAY 17, 2021

1) What Is Data Discovery? 2) Why is Data Discovery So Popular? 3) Data Discovery Tools Attributes. 5) How To Perform Smart Data Discovery. 6) Data Discovery For The Modern Age. We live in a time where data is all around us. So, what is data discovery?

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ElegantJ BI

MARCH 19, 2021

When considering the advantages of data popularity and sharing, one must also consider that not all popular data will be high-quality data (and vice versa). So, there is definitely a need to provide both approaches in data analysis.

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ElegantJ BI

MARCH 19, 2021

When considering the advantages of data popularity and sharing, one must also consider that not all popular data will be high-quality data (and vice versa). So, there is definitely a need to provide both approaches in data analysis. Original Post : Data Agility and ‘Popularity’?

Data Quality 130

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ElegantJ BI

MARCH 19, 2021

When considering the advantages of data popularity and sharing, one must also consider that not all popular data will be high-quality data (and vice versa). So, there is definitely a need to provide both approaches in data analysis. Original Post : Data Agility and ‘Popularity’?

Data Quality 130

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Astera

OCTOBER 30, 2024

This is because the integration of AI transforms the static repository into a dynamic, self-improving system that not only stores metadata but also enhances data context and accessibility to drive smarter decision-making across the organization. And when everyone has easy access to data, they can collaborate and meet demands more effectively.

Data Discovery 52

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Dataversity

SEPTEMBER 12, 2024

You want to implement data democratization, so you deployed all the new tooling and data infrastructure. You have a data catalog to manage metadata and ensure data lineage and a data marketplace to enable data discovery and self-service analytics.

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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

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Astera

JUNE 14, 2024

Instead of relying solely on manual efforts, automated data governance uses reproducible processes to maintain data quality, enrich data assets, and simplify workflows. This approach streamlines data management, maintains data integrity, and ensures consistent data quality and context over time.

Data Governance 40

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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

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Astera

AUGUST 28, 2024

Ideal for: user-friendly data exploration and self-service analytics, well-suited for businesses of all sizes with a focus on intuitive data discovery. SAS Viya SAS Viya is an AI-powered, in-memory analytics engine that offers data visualization, reporting, and analytics for businesses.

IBM Support 40

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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 Discovery 173

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Astera

DECEMBER 6, 2024

This blog addresses the NLP vs. LLM debate by discussing what they are, their differences, and their use cases. LLMs can simplify complex data integration processes by crafting data mapping suggestions, or identifying schema mismatches when consolidating data from multiple sources.

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