IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. As a result, organizations have spent untold money and time gathering and integrating data.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

IBM Big Data Hub

OCTOBER 30, 2023

AWS’s secure and scalable environment ensures data integrity while providing the computational power needed for advanced analytics. Thus, DB2 PureScale on AWS equips this insurance company to innovate and make data-driven decisions rapidly, maintaining a competitive edge in a saturated market.

Insurance 85

Insurance Data Warehouse Data-driven Unstructured Data 85

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. Summary AWS Data Quality is now Generally Available.

Data Quality 93

Data Quality Statistics Data Lake Visualization 93

erwin

APRIL 27, 2022

In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Change Data Capture identifies and processes only the data that has changed and stores the changed data in a form so as to be of further use.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

BizAcuity

MAY 16, 2022

To stay relevant in the market and to increase brand awareness, organizations use big data analytics and business intelligence to navigate their way after getting a full understanding of their ideal customers and their behavior before and during the buying journey. So, make sure you have a data strategy in place. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

FEBRUARY 9, 2023

To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications. One widely used approach is getting the CRM data into your data warehouse and keeping it up to date through frequent data synchronization.

Data Warehouse 74

Data Warehouse Data-driven Snapshot Testing 74

Data Virtualization

FEBRUARY 24, 2022

We say that data storage, like matter, adheres to the Law of Increments, which states that, according. The post Introducing the Liquid Data Model appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Modeling 59

Modeling Data Integration Software Management 59

Cloudera

MAY 16, 2019

The conference provides a useful opportunity to reflect on the rapid evolution we’ve seen in the Data Integration and Management space, much of it driven by the innovations that Cloudera and the open source community have been delivering. The traditional Data Warehouse ETL process has splintered into many smaller components.

Analytics 40

Analytics Data Warehouse Data-driven Data Integration 40

Data Virtualization

OCTOBER 5, 2022

For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.

Data Lake 52

Data Lake Data Architecture Data Integration Management 52

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. In this blog, we share our takeaways as they relate to the DMSA market trends. 3. Expansion beyond core data management. Cloudera’s Positioning.

Management 42

Management Metadata Analytics Machine Learning 42

IBM Big Data Hub

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

JULY 31, 2023

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand. For IAM role ¸ choose GlueBlogRole.

Sales 52

Sales Data Warehouse Visualization Testing 52

erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Data Virtualization

MARCH 3, 2021

To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is. The post Data Management Challenges for the Modern Enterprise appeared first on Data Virtualization blog.

Enterprise 76

Enterprise Management Strategy Data Lake 76

Data Virtualization

OCTOBER 7, 2021

The post Rapidly Enable Tangible Business Value through Data Virtualization (Data minimization) appeared first on Data Virtualization blog.

Digital Transformation 52

Digital Transformation Data Lake Data Warehouse Data Integration 52

erwin

DECEMBER 12, 2019

Here are some benefits of metadata management for data governance use cases: Better Data Quality: Data issues and inconsistencies within integrated data sources or targets are identified in real time to improve overall data quality by increasing time to insights and/or repair. by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Data Virtualization

FEBRUARY 17, 2021

We need to be able to develop insights from data, and act on. The post Build a Virtual Data Mart with the Denodo Platform in Just 10 Minutes appeared first on Data Virtualization blog.

Analytics 52

Analytics Data Warehouse Data Integration Big Data 52

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 92

Data Lake Data Warehouse Metadata Data Architecture 92

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 95

Analytics Visualization Data Integration Cost-Benefit 95

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Today, data integration platforms like Rivery do just that.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Genie — Distributed big data orchestration service by Netflix.

Testing 307

Testing Machine Learning Consulting Data Quality 307

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

Data Warehouse 94

Data Warehouse Data Integration Marketing Software 94

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. He works based in Tokyo, Japan.

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 67

Modeling Sales Data Warehouse Snapshot 67

AWS Big Data

JULY 12, 2023

This blog post is co-written with Zygimantas Koncius from Etleap. Organizations use their data to extract valuable insights and drive informed business decisions. Introduction to Amazon Redshift Amazon Redshift is a fast, fully-managed, self-learning, self-tuning, petabyte-scale, ANSI-SQL compatible, and secure cloud data warehouse.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

Cloudera

NOVEMBER 2, 2020

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

Data Warehouse 91

Data Warehouse Optimization Dashboards Interactive 91

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. One of the most common use cases for data preparation on Amazon Redshift is to ingest and transform data from different data stores into an Amazon Redshift data warehouse.

Visualization 75

Visualization Data Warehouse Big Data Data Lake 75

IBM Big Data Hub

APRIL 19, 2023

This work involved creating a single set of definitions and procedures for collecting and reporting financial data. The water company also needed to develop reporting for a data warehouse, financial data integration and operations.

Technology 89

Technology Forecasting Data Warehouse Reporting 89

IBM Big Data Hub

APRIL 27, 2022

The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. Read: The first capability of a data fabric is a semantic knowledge data catalog, but what are the other 5 core capabilities of a data fabric? 11 May 2021. .

Management 87

Management Metadata Data Architecture Data Lake 87

CDW Research Hub

NOVEMBER 17, 2021

Before big data and the cloud, it wasn’t a big deal for organizations to create and manage their own data. Streamlining data into one source frees up storage and relieves IT stress in buying storage that may not be needed. ETL helps handle data integrity issues so that everyone is always working with fresh data.

Strategy 83

Strategy Data Governance Data Warehouse Data-driven 83

erwin

FEBRUARY 19, 2021

It harvests metadata from various data sources and maps any data element from source to target and harmonize data integration across platforms. With this accurate picture of your metadata landscape, you can accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric. Simply put? Spoiler alert!

Metadata 52

Metadata IT Metrics Data-driven 52

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

BizAcuity

AUGUST 1, 2022

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Data Security. Trend Indicators.

Reporting 52

Reporting OLAP Online Analytical Processing Dashboards 52

Sisense

JULY 22, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways organizations tackle the challenges of this new world to help their companies and their customers thrive. Data modeling: Create relationships between data.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98