Astera

FEBRUARY 28, 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

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

NOVEMBER 1, 2023

Businesses rely heavily on various technologies to manage and analyze their growing amounts of data. Data warehouses and databases are two key technologies that play a crucial role in data management. What is a Data Warehouse?

Data Warehouse 40

Data Warehouse Real-time Data E-Commerce Data Governance 40

Astera

APRIL 27, 2023

Data Lake Vs Data Warehouse Every business needs to store, analyze, and make decisions based on data. To do this, they must choose between two popular data storage technologies: data lakes and data warehouses. What is a Data Lake? What is a Data Warehouse?

Data Warehouse 52

Data Warehouse Cloud Computing Data Management Data Governance 52

BizAcuity

APRIL 14, 2022

Big Data Ecosystem. Big data paved the way for organizations to get better at what they do. Data management and analytics are a part of a massive, almost unseen ecosystem which lets you leverage data for valuable insights. Data Management. Unscalable data architecture. Slow query performance.

Big Data 130

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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 Government Data Warehouse 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

JANUARY 29, 2024

Their perspectives offer valuable guidance for enterprises striving to safeguard their data in 2024 and beyond. These insights touch upon: The growing importance of protecting data. The role of data governance. Resolving data security issues. The impact of industry regulations. Emergence of new technologies.

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Dataversity

APRIL 5, 2021

However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY. Agility is key to success here.

Data Management 244

Data Management Agile Data Warehouse Data Modelling 244

Astera

AUGUST 29, 2024

It enables easy data sharing and collaboration across teams, improving productivity and reducing operational costs. Identifying Issues Effective data integration manages risks associated with M&A. It includes: Identifying Data Sources involves determining the specific systems and databases that contain relevant data.

Data Governance 52

Data Governance Data Warehouse Data Quality Government 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

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 75

IBM Maintenance Data Warehouse IBM cost Data Quality 75

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

Astera

JULY 3, 2024

Data architecture is important because designing a structured framework helps avoid data silos and inefficiencies, enabling smooth data flow across various systems and departments. An effective data architecture supports modern tools and platforms, from database management systems to business intelligence and AI applications.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

Actian

JULY 26, 2019

So, you have made the business case to modernize your data warehouse. But how do you effectively go about choosing the right data warehouse to migrate to? Should you stay with your existing traditional data warehouse provider as they try to convince you to stay on-premise with their latest appliance?

Data Warehouse 40

Data Warehouse Government Predictive Analytics Banking 40

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

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

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

NOVEMBER 30, 2023

With rising data volumes, dynamic modeling requirements, and the need for improved operational efficiency, enterprises must equip themselves with smart solutions for efficient data management and analysis. This is where Data Vault 2.0 It supersedes Data Vault 1.0, What’s New in Data Vault 2.0? Data Vault 2.0

Data Warehouse 52

Data Warehouse Big Data Healthcare Data Governance 52

Astera

SEPTEMBER 4, 2024

This feature automates communication and insight-sharing so your teams can use, interpret, and analyze other domain-specific data sets with minimal technical expertise. Shared data governance is crucial to ensuring data quality, security, and compliance without compromising on the flexibility afforded to your teams by the data mesh approach.

Data Architecture 52

Data Architecture Data Governance Government Data Discovery 52

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

AUGUST 13, 2024

After modernizing and transferring the data, users access features such as interactive visualization, advanced analytics, machine learning, and mobile access through user-friendly interfaces and dashboards. What is Data-First Modernization? It involves a series of steps to upgrade data, tools, and infrastructure.

Data Governance 52

Data Governance Data Architecture Data Quality Real-time Data 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 […].

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Data Warehouse Data Quality Data Governance Government 173

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 Quality Data Governance Master Data Management 40

Astera

JANUARY 18, 2024

Fivetran is a low-code/no-code ELT (Extract, load and transform) solution that allows users to extract data from multiple sources and load it into the destination of their choice, such as a data warehouse. It also offers limited data transformation capabilities and that too through dbt core, which is an open source tool.

Data Warehouse 52

Data Warehouse Data Quality Data Management Government 52

Astera

APRIL 3, 2024

As important as it is to know what a data quality framework is, it’s equally important to understand what it isn’t: It’s not a standalone concept—the framework integrates with data governance, security, and integration practices to create a holistic data ecosystem. Why do you need a data quality framework?

Data Quality 52

Data Quality Data Governance Government Monitoring 52

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

Smart Data Collective

OCTOBER 17, 2022

Cloud data warehouses provide various advantages, including the ability to be more scalable and elastic than conventional warehouses. Can’t get to the data. All of this data might be overwhelming for engineers who struggle to pull in data sets quickly enough. Data pipeline maintenance.

Big Data 272

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Tableau

MAY 11, 2022

They rank disconnected data and systems among their biggest challenges alongside budget constraints and competing priorities. Data fabrics are gaining momentum as the data management design for today’s challenging data ecosystems. Throughout the years, we’ve tackled the challenge of data and content reuse.

Data Warehouse 98

Data Warehouse Government Artificial Intelligence Data Discovery 98

Tableau

MAY 11, 2022

They rank disconnected data and systems among their biggest challenges alongside budget constraints and competing priorities. Data fabrics are gaining momentum as the data management design for today’s challenging data ecosystems. Throughout the years, we’ve tackled the challenge of data and content reuse.

Data Warehouse 98

Data Warehouse Government Artificial Intelligence Data Discovery 98

Astera

JANUARY 25, 2024

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.

E-Commerce 52

E-Commerce Data Warehouse Retail Customer Experience 52

Domo

JULY 23, 2024

Despite advancements in data engineering and predictive modeling, chief information officers (CIOs) face the tough challenge of making data accessible and breaking down silos that hinder progress. This fragmentation creates “BI breadlines,” where data requests pile up and slow down progress.

Data Warehouse 52

Data Warehouse Data Security Data Architecture Government 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

Astera

JANUARY 18, 2024

Data Quality : It includes features for data quality management , ensuring that the integrated data is accurate and consistent. Data Governance : Talend’s platform offers features that can help users maintain data integrity and compliance with governance standards.

IBM Support 52

IBM Support IBM Maintenance IBM cost Data Warehouse 52

Astera

MAY 14, 2024

Master data management vs. Metadata management Before proceeding, it’s essential to clarify that while both master data management (MDM) and metadata management are crucial components of data management and governance, they are two unique concepts and, therefore, not interchangeable.

Government 52

Government Data Governance Master Data Management Documentation 52

Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

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