Astera

JANUARY 29, 2024

These insights touch upon: The growing importance of protecting data. The role of data governance. Resolving data security issues. “Data privacy is becoming more and more important as our data resides with so many companies. The impact of industry regulations. Balancing the benefits and risks of AI.

Government 145

Government Data Warehouse Data Governance Digital 145

Domo

APRIL 30, 2021

Digital transformation efforts are placing a sharp focus on disparate data sources. As companies aim to speed business value, they’re realizing the need for data agility. But they’ve got a problem: Most data sits in segmented silos, warehouses, data lakes, databases, and even spreadsheets.

Data Warehouse 98

Data Warehouse Artificial Intelligence Government Digital Transformation 98

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

Domo

MAY 24, 2021

According to Gartner , data integration is “the consistent access and delivery of data across the spectrum of data subject areas and data structure types in the enterprise to meet the data consumption requirements of all applications and business processes.”

Government 136

Government Data Architecture Business Intelligence Business Intelligence 136

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

OCTOBER 27, 2023

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

BizAcuity

APRIL 1, 2023

Introduction Informatica is a data integration tool based on ETL architecture. It provides data integration software and services for various businesses, industries and government organizations including telecommunication, health care, financial and insurance services.

Data Warehouse 130

Data Warehouse Government Documentation Monitoring 130

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

Dataversity

APRIL 5, 2021

Agility is key to success here. 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. Click to learn more about author Kendall Clark.

Data Management 244

Data Management Agile Data Warehouse Data Modelling 244

Domo

JUNE 15, 2022

That means your data apps can run on Snowflake right alongside data stored in Domo—and even alongside your Databricks lakehouse—in one seamless experience. No moving or copying data—ever. You get all of this agility with none of the expected trade-offs in performance.

Cloud Computing 86

Cloud Computing Data Governance Data Warehouse Government 86

ElegantJ BI

DECEMBER 7, 2017

In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to data warehouses and data marts and lots of complicated massaging and manipulation of data across other data sources.

Supply Chain 130

Supply Chain Data Discovery Data Warehouse Government 130

ElegantJ BI

DECEMBER 7, 2017

In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to data warehouses and data marts and lots of complicated massaging and manipulation of data across other data sources.

Supply Chain 130

Supply Chain Data Discovery Data Warehouse Government 130

ElegantJ BI

DECEMBER 7, 2017

In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to data warehouses and data marts and lots of complicated massaging and manipulation of data across other data sources.

Supply Chain 130

Supply Chain Data Discovery Data Warehouse Business Intelligence 130

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Innovation 101

Innovation Data Warehouse Data Architecture Visualization 101

ElegantJ BI

OCTOBER 1, 2020

Instead, the average business user can gather and prepare data on their own with clear insight into the sources and methods so that the outcome meets requirements. What the business needs is a tool that allows users to prepare and analyze data and satisfy the needs of today.

Data Discovery 130

Data Discovery Data Warehouse Business Intelligence Business Intelligence 130

ElegantJ BI

OCTOBER 1, 2020

Instead, the average business user can gather and prepare data on their own with clear insight into the sources and methods so that the outcome meets requirements. What the business needs is a tool that allows users to prepare and analyze data and satisfy the needs of today.

Data Discovery 130

Data Discovery Data Warehouse Government Business Intelligence 130

Tableau

MAY 11, 2022

At their most basic level, data fabrics leverage artificial intelligence and machine learning to unify and securely manage disparate data sources without migrating them to a centralized location. Data fabric governance assumes a federated environment, so they scale by connecting to new data sources as they emerge.

Data Warehouse 98

Data Warehouse Government Artificial Intelligence Data Discovery 98

Tableau

MAY 11, 2022

At their most basic level, data fabrics leverage artificial intelligence and machine learning to unify and securely manage disparate data sources without migrating them to a centralized location. Data fabric governance assumes a federated environment, so they scale by connecting to new data sources as they emerge.

Data Warehouse 98

Data Warehouse Government Artificial Intelligence Data Discovery 98

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. Information marts are data structures optimized for reporting and analysis.

Agile 52

Agile Data Warehouse Data Quality Government 52

BizAcuity

DECEMBER 28, 2022

Informatica is a data integration tool based on ETL architecture. It provides data integration software and services for various businesses, industries and government organizations including telecommunication, health care, financial and insurance services. Data is moved from many databases to the Data warehouse.

Data Warehouse 100

Data Warehouse Government Documentation Monitoring 100

Business Analysis Knowledge Share

OCTOBER 24, 2023

Data Warehousing is the process of collecting, storing, and managing data from various sources into a central repository. This repository, often referred to as a data warehouse , is specifically designed for query and analysis. Data Sources Data Warehouses collect data from diverse sources within an organization.

IBM Maintenance 75

IBM Maintenance Data Warehouse IBM cost Data Quality 75

Actian

JULY 26, 2019

So, you have made the business case to modernize your data warehouse. A modernization project, done correctly can deliver compelling and predictable results to your organization including millions in cost savings, new analytics capabilities and greater agility. For more information go to Actian Avalanche cloud data warehouse.

Data Warehouse 40

Data Warehouse Government Predictive Analytics Banking 40

Actian

FEBRUARY 13, 2020

Does your company have a real-time connected data warehouse where you can aggregate data flowing in from all of your IT systems together with streaming data from IoT, mobile, and SaaS services? The first article looked at manufacturing operations and integrating data across your supply chain.

Data Warehouse 40

Data Warehouse Supply Chain Enterprise Architecture Digital Transformation 40

Domo

JULY 23, 2024

Breaking down data silos: the CIO’s dilemma Enterprise data is often stuck in silos—scattered across business systems, SaaS applications, and data warehouses. 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

Domo

OCTOBER 22, 2021

All too often, enterprise data is siloed across various business systems, SaaS systems, and enterprise data warehouses, leading to shadow IT and “BI breadlines”—a long queue of BI requests that can keep getting longer, compounding unresolved requests for data engineering services. The bottom line.

Data Warehouse 52

Data Warehouse Embedded Analytics Government Digital Transformation 52

Actian

JANUARY 7, 2019

This is the essence of business agility. Historical reports and batch data from last night or last week don’t provide leaders with the information and actionable insights they need to lead the company effectively – they need real-time data (and plenty of it!). What it means to be agile. Agility requires real-time data.

Real-time Data 40

Real-time Data Agile Supply Chain Data Warehouse 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 its foundation rooted in scalable hub-and-spoke architecture, Data Vault 1.0 provided a framework for traceable, auditable, and flexible data management in complex business environments. Building upon the strengths of its predecessor, Data Vault 2.0 Data Vault 2.0 What’s New in Data Vault 2.0? Data Vault 2.0

Data Warehouse 52

Data Warehouse Big Data Healthcare Data Governance 52

Actian

OCTOBER 7, 2019

A data hub is a logical architecture which enables data sharing by connecting producers of data (applications, processes, and teams) with consumers of data (other applications, process, and teams). Point-to-point data integration, however, will slow your operations and progress and deny you the achievement of your goal.

Data Warehouse 10

Data Warehouse Government Data Governance Agile 10

Astera

JANUARY 2, 2024

Free Download Here’s what the data management process generally looks like: Gathering Data: The process begins with the collection of raw data from various sources. Once collected, the data needs a home, so it’s stored in databases, data warehouses , or other storage systems, ensuring it’s easily accessible when needed.

Data Management 52

Data Management Data Warehouse Data Governance Data Quality 52

Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

Innovation 52

Innovation Data Warehouse Data Architecture Visualization 52

Astera

JULY 3, 2024

It creates a space for a scalable environment that can handle growing data, making it easier to implement and integrate new technologies. Moreover, a well-designed data architecture enhances data security and compliance by defining clear protocols for data governance.

Data Architecture 40

Data Architecture Data Warehouse Data Governance Government 40

Actian

NOVEMBER 26, 2019

The Challenges of Connecting Disparate Data Sources and Migrating to a Cloud Data Warehouse. Migrating to a cloud data warehouse makes strategic sense in the modern context of cloud services and digital transformation. Conceptually, it is easy to understand why you would want to move to a cloud data warehouse.

Data Warehouse 8

Data Warehouse Vision Digital Transformation Digital 8

Actian

JUNE 10, 2019

This includes both ready-to-use SaaS solutions as well as cloud-based infrastructure (IaaS and Paas) for various needs, such as data warehouses and in-house developed applications. Data warehouse migration to the cloud. During the past few years, Hadoop has been the big trend in data warehousing.

Data Management 40

Data Management Data Warehouse Big Data Data Governance 40

Sisense

OCTOBER 14, 2020

Today, data teams form a foundational element of startups and are an increasingly prominent part of growing existing businesses because they are instrumental in helping their companies analyze the huge volumes of data that they must deal with. This combination has given the team advanced data handling and analytics capabilities.

Data Modelling 98

Data Modelling Embedded Analytics Data Warehouse Innovation 98