The Data Administration Newsletter

MAY 16, 2023

Data quality management (DQM) has advanced considerably over the years. The full extent of the problem was first recognized during the data warehouse movement in the 1980s.

Data Quality 52

Data Quality Data Warehouse Master Data Management Data Governance 52

Actian

JUNE 10, 2019

2019 is becoming an exciting year for the data management community. While trends are important building blocks about how companies approach their data management today, they are also providing insights into future capabilities to incorporate the individual pieces into a holistic, integrated solution.

Data Management 40

Data Management Data Warehouse Big Data Data Governance 40

Dataversity

MAY 31, 2021

As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. The post Dear Laura: Should We Hire Full-Time Data Stewards? Click to learn more about author Laura Madsen. Welcome to the Dear Laura blog series! Last year I wrote […].

Data Governance 246

Data Governance Government Master Data Management Data Warehouse 246

Astera

MAY 25, 2023

That’s how it can feel when trying to grapple with the complexity of managing data on the cloud-native Snowflake platform. They range from managing data quality and ensuring data security to managing costs, improving performance, and ensuring the platform can meet future needs.

Data Quality 52

Data Quality Government Data Governance Monitoring 52

Astera

NOVEMBER 27, 2023

Clean and accurate data is the foundation of an organization’s decision-making processes. However, studies reveal that only 3% of the data in an organization meets basic data quality standards, making it necessary to prepare data effectively before analysis. This is where data profiling comes into play.

Data Mining 52

Data Mining Data Quality Data Governance Business Intelligence 52

Dataversity

DECEMBER 16, 2020

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

Data Warehouse 173

Data Warehouse Data Quality Data Governance Government 173

The Data Administration Newsletter

FEBRUARY 1, 2022

In this blog, we will discuss a common problem for data warehouses that are designed to maintain data quality and provide evidence of accuracy. Without verification, the data can’t be trusted. Enter the mundane, but necessary, task of data reconciliation. This is often a time-consuming and wasteful process.

Government 59

Government Data Warehouse Data Quality Data Governance 59

Astera

JUNE 6, 2023

The best data pipeline tools offer the necessary infrastructure to automate data workflows, ensuring impeccable data quality, reliability, and timely availability. Empowering data engineers and analysts, these tools streamline data processing, integrate diverse sources, and establish robust data governance practices.

Data Warehouse 52

Data Warehouse Monitoring Real-time Data Documentation 52

Domo

JULY 8, 2021

It’s also important to think about how you’re going to manage your cloud vendors/providers. In order to manage your infrastructure such as networks, storage, services, data management, and virtualization, you’ll likely be working with several cloud providers, including cloud data integration and cloud BI providers.

Data Governance 52

Data Governance Government Embedded Analytics Data Warehouse 52

Astera

NOVEMBER 16, 2022

Understand and assess potential data quality challenges in a hybrid cloud environment. Implement proper data validation rules and policies to ensure data accuracy and completeness. Evaluate the location of your data. Automation will help you save time and costs as well as undertake big data initiatives.

Data Architecture 52

Data Architecture Data Quality Data Warehouse Data Governance 52

Astera

JUNE 13, 2023

Acting as a conduit for data, it enables efficient processing, transformation, and delivery to the desired location. By orchestrating these processes, data pipelines streamline data operations and enhance data quality. Stream processing platforms handle the continuous flow of data, enabling real-time insights.

E-Commerce 52

E-Commerce Data Quality Real-time Data Data Warehouse 52

ElegantJ BI

SEPTEMBER 30, 2021

When a business enters the domain of data management, it is easy to get lost in a flurry of promises, brochures, demos and the promise of the future. In this article, we will present the factors and considerations involved in choosing the right data management solution for your business.

Data Management 130

Data Management Data Warehouse Data Governance Government 130

ElegantJ BI

SEPTEMBER 30, 2021

When a business enters the domain of data management, it is easy to get lost in a flurry of promises, brochures, demos and the promise of the future. In this article, we will present the factors and considerations involved in choosing the right data management solution for your business. Data Warehouse.

Data Management 130

Data Management Data Warehouse Data Governance Government 130

Astera

OCTOBER 31, 2023

Data preparation (also known as data prep ) is the process of standardizing data into the desired output. By converting unstructured data into a structured format, data preparation enables comprehensive data analysis that can reveal hidden insights and opportunities.

Data Quality 52

Data Quality Documentation Data Warehouse Data Governance 52

ElegantJ BI

SEPTEMBER 30, 2021

When a business enters the domain of data management, it is easy to get lost in a flurry of promises, brochures, demos and the promise of the future. In this article, we will present the factors and considerations involved in choosing the right data management solution for your business. Data Warehouse.

Data Management 130

Data Management Data Warehouse Data Governance Government 130

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 megabytes of data every second?

Big Data 130

Big Data Data Analytics Data Analytics Data Management 130

Dataversity

AUGUST 5, 2021

According to Gartner, data fabric is an architecture and set of data services that provides consistent functionality across a variety of environments, from on-premises to the cloud. Data fabric simplifies and integrates on-premises and cloud Data Management by accelerating digital transformation.

Digital Transformation 246

Digital Transformation Digital Data Management Data Warehouse 246

Astera

APRIL 3, 2024

What is a data quality framework? A data quality framework is a set of guidelines that enable you to measure, improve, and maintain the quality of data in your organization. It’s not a magic bullet—data quality is an ongoing process, and the framework is what provides it a structure.

Data Quality 52

Data Quality Data Governance Government Monitoring 52

Astera

AUGUST 8, 2023

What matters is how accurate, complete and reliable that data. Data quality is not just a minor detail; it is the foundation upon which organizations make informed decisions, formulate effective strategies, and gain a competitive edge. to help clean, transform, and integrate your data.

Data Quality 52

Data Quality IBM Support IBM Maintenance Monitoring 52

Astera

JANUARY 1, 2024

What Is Data Quality? Data quality is the measure of data health across several dimensions, such as accuracy, completeness, consistency, reliability, etc. In short, the quality of your data directly impacts the effectiveness of your decisions.

Data Quality 52

Data Quality Data Governance Government Data Warehouse 52

Astera

JANUARY 1, 2024

What Is Data Quality? Data quality is the measure of data health across several dimensions, such as accuracy, completeness, consistency, reliability, etc. In short, the quality of your data directly impacts the effectiveness of your decisions.

Data Quality 52

Data Quality Data Governance Government Data Warehouse 52

Astera

MARCH 20, 2024

This article covers everything about enterprise data management, including its definition, components, comparison with master data management, benefits, and best practices. What Is Enterprise Data Management (EDM)? Why is Enterprise Data Management Important?

Data Management 52

Data Management Master Data Management Data Warehouse Government 52

Astera

JANUARY 2, 2024

Relying on this data to power business decisions is like setting sail without a map. This is why organizations have effective data management in place. But what exactly is data management? What Is Data Management? As businesses evolve, so does their data.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Astera

NOVEMBER 13, 2023

But have you ever wondered how data informs the decision-making process? The key to leveraging data lies in how well it is organized and how reliable it is, something that an Enterprise Data Warehouse (EDW) can help with. What is an Enterprise Data Warehouse (EDW)?

Data Warehouse 52

Data Warehouse E-Commerce Supply Chain Real-time Data 52

Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

FEBRUARY 27, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

Astera

APRIL 24, 2024

There are different types of data ingestion tools, each catering to the specific aspect of data handling. Standalone Data Ingestion Tools : These focus on efficiently capturing and delivering data to target systems like data lakes and data warehouses.

Data Warehouse 52

Data Warehouse Real-time Data Documentation Data Quality 52

BizAcuity

APRIL 1, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. Data governance and security measures are critical components of data strategy.

Business Intelligence 130

Business Intelligence Business Intelligence Data Warehouse Data Mining 130

BizAcuity

JANUARY 31, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. Data governance and security measures are critical components of data strategy.

Business Intelligence 130

Business Intelligence Business Intelligence Data Warehouse Data Mining 130

Business Analysis Knowledge Share

OCTOBER 24, 2023

This article aims to provide a comprehensive overview of Data Warehousing, breaking down key concepts that every Business Analyst should know. Introduction As businesses generate and accumulate vast amounts of data, the need for efficient data management and analysis becomes paramount.

IBM Maintenance 73

IBM Maintenance Data Warehouse IBM cost Data Quality 73

Astera

MARCH 28, 2024

So, organizations create a data governance strategy for managing their data, and an important part of this strategy is building a data catalog. They enable organizations to efficiently manage data by facilitating discovery, lineage tracking, and governance enforcement.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

Astera

JANUARY 15, 2024

Push-down ELT technology: Matillion utilizes push-down ELT technology, which pushes transformations down to the data warehouse for efficient processing. Automation and scheduling: You can automate data pipelines and schedule them to run at specific times. ETL and data mapping automation based on triggers and time intervals.

Data Warehouse 52

Data Warehouse Real-time Data Data Quality Visualization 52

Astera

FEBRUARY 9, 2024

Financial data integration faces many challenges that hinder its effectiveness and efficiency in detecting and preventing fraud. Challenges of Financial Data Integration Data Quality and Availability Data quality and availability are crucial for any data integration project, especially for fraud detection.

IBM Support 52

IBM Support Data Quality IBM Maintenance Data Governance 52

Business Analysis Knowledge Share

MARCH 15, 2023

Understanding the key concepts of data warehousing, such as data integration, dimensional modeling, OLAP, and data marts, is vital for business analysts who are responsible for analyzing data and providing insights that drive business performance. What is Data Warehousing?

Big Data 52

Big Data Data Analytics Data Analytics Data Warehouse 52

Astera

OCTOBER 10, 2023

One of the first steps in the data management cycle is data mapping. Data mapping is the process of defining how data elements in one system or format correspond to those in another. Another benefit of data mapping in data integration is improved data quality management.

IBM Maintenance 52

IBM Maintenance IBM Support IBM cost Data Quality 52

Astera

MARCH 30, 2023

At the fundamental level, data sharing is the process of making a set of data resources available to individuals, departments, business units or even other organizations. Moreover, data sharing leads to better data governance by centralizing their data and ensuring that it is consistent, accurate, and updated.

Data Quality 52

Data Quality Data Warehouse Data Security Finance 52

Astera

JULY 13, 2023

This process includes moving data from its original locations, transforming and cleaning it as needed, and storing it in a central repository. Data integration can be challenging because data can come from a variety of sources, such as different databases, spreadsheets, and data warehouses.

Data Warehouse 40

Data Warehouse Data Governance Data Quality Master Data Management 40