erwin

MAY 2, 2022

I’m not proposing that business logic be held in the database, but it needs to be documented in the data model even if it will be implemented in application code. No matter where you implement it, you must fully document the business requirements in order to produce an effective final result.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

AWS Big Data

OCTOBER 20, 2023

Regarding the Azure Data Lake Storage Gen2 Connector, we highlight any major differences in this post. AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning, and application development. Learn more in README.

Data Lake 82

Data Lake Big Data Consulting Data Warehouse 82

Sisense

JULY 2, 2020

Many popular cloud analysis tools, including Sisense for Cloud Data Teams, support both on-premise database servers and cloud data warehouses. When companies use cloud applications (for example, Salesforce) they need to get that data from the cloud and into their databases for analysis. Connections to Data Sources.

Data Warehouse 98

Data Warehouse Data Integration Software Marketing 98

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

Jet Global

OCTOBER 7, 2020

Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities. The Data Entity Store is an internal data warehouse that is only available to embedded Power BI reports (not the full version of Power BI).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

MAY 1, 2020

We can almost guarantee you different results from each, and you end up with no data integrity whatsoever. The mechanical solution is to build a data warehouse. This is because people won’t use BI applications that are founded on irrelevant, incomplete, or questionable data. Risk to the business. It will pay off.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

Octopai

JUNE 1, 2020

Data mapping is the cornerstone of many important business intelligence processes: Data Integration – Even if systems are compatible, combining two disparate data repositories still requires meticulous data mapping. Correct data mapping facilitates the creation of usable, searchable data warehouses.

Metadata 52

Metadata Data Warehouse Data Integration Enterprise 52

AWS Big Data

FEBRUARY 8, 2023

Vyaire developed a custom data integration platform, iDataHub, powered by AWS services such as AWS Glue , AWS Lambda , and Amazon API Gateway. In this post, we share how we extracted data from SAP ERP using AWS Glue and the SAP SDK. To learn more about AWS Glue, check out AWS Glue Documentation.

Testing 71

Testing Data Integration Data Lake Enterprise 71

erwin

JANUARY 11, 2019

A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management. The problem usually starts by relying on manual integration methods for data preparation and mapping.

Data Governance 40

Data Governance Risk Metadata Management 40

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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. Choose Run to run the job.

Sales 52

Sales Data Warehouse Visualization Testing 52

CIO Business Intelligence

JUNE 7, 2022

Because of this, only a small percentage of your AI team will work on data science efforts, he says. The rest of the team will identify the problem being solved, help explain the data, help organize the data, integrate the output into another production system, or present the data in a presentation-ready manner.”.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. They are opting for cloud data services more frequently.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 78

Data Lake Data Warehouse Data-driven Optimization 78

AWS Big Data

JULY 25, 2023

The integration of Talend Cloud and Talend Stitch with Amazon Redshift Serverless can help you achieve successful business outcomes without data warehouse infrastructure management. Data scientists, developers, and data analysts can access meaningful insights and build data-driven applications with zero maintenance.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. Data ingestion/integration services. Reverse ETL tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

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 93

Analytics Visualization Data Integration Cost-Benefit 93

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. It could be utilized as a tool for cleansing data.

IT 52

IT Data Warehouse Cost-Benefit Data Integration 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.

IT 40

IT Data Warehouse Cost-Benefit Data Integration 40

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

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions. Choose the Data quality tab.

Data Quality 73

Data Quality Data Lake Data-driven Metrics 73

Cloudera

APRIL 14, 2021

Precisely Data Integration, Change Data Capture and Data Quality tools support CDP Public Cloud as well as CDP Private Cloud. Using the CDE Integration API: CDE provides a robust API for integration with your existing continuous integration/continuous delivery platforms.

Data Warehouse 80

Data Warehouse Data Processing Data Quality Machine Learning 80

IBM Big Data Hub

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

Cost-Benefit 81

Cost-Benefit Metadata Data Governance Modeling 81

Jedox

MARCH 11, 2021

A data silo typically consists of stored data that is not available to the entire organization, but only to some parts of it, such as departments, teams, or even individual employees, and is thus siloed within the organization. They are contrary to the approach of a data warehouse. So that’s it? No, not yet.

Sales 80

Sales Optimization Digital Transformation Data Warehouse 80

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Sisense

JULY 22, 2020

In all cases the data will eventually be loaded into a different place, so it can be managed, and organized, using a package such as Sisense for Cloud Data Teams. Using data pipelines and data integration between data storage tools, engineers perform ETL (Extract, transform and load). Connect tables.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

BI-Survey

NOVEMBER 23, 2021

The transactional data was stored in isolated data sets and initially served only one purpose, namely, to document the transaction that had taken place. Over time, enterprises realized that data is worth more. However, the operational data stored in data silos was not suitable for this task.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 100

Data Lake Management Metrics Data Warehouse 100

AWS Big Data

OCTOBER 5, 2023

In today’s data-driven world, the ability to effortlessly move and analyze data across diverse platforms is essential. Amazon AppFlow , a fully managed data integration service, has been at the forefront of streamlining data transfer between AWS services, software as a service (SaaS) applications, and now Google BigQuery.

Data Warehouse 83

Data Warehouse Machine Learning Data Integration Data-driven 83

CIO Business Intelligence

NOVEMBER 7, 2023

Centralized reporting boosts data value For more than a decade, pediatric health system Phoenix Children’s has operated a data warehouse containing more than 120 separate data systems, providing the ability to connect data from disparate systems. Companies should also incorporate data discovery, Higginson says.

Data Warehouse 142

Data Warehouse Digital Transformation Reporting Data-driven 142

datapine

FEBRUARY 22, 2022

They can govern the implementation with a documented business case and be responsible for changes in scope. IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Find a way to integrate it into the new strategy, or you will have upset employees. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

AWS Big Data

APRIL 25, 2023

The following factors guided our decision: Tool close to data – It was important to have the data visualization tool as close to the data as possible. At Dafiti, the entire infrastructure is on AWS, and we use Amazon Redshift as our Data Warehouse.

Visualization 52

Visualization IT Data-driven Reporting 52

erwin

JULY 17, 2019

It improves IT and business data literacy and knowledge, supporting enterprise data governance and business enablement. It helps solve the lack of visibility and control over “data at rest” in databases, data lakes and data warehouses and “data in motion” as it is integrated with and used by key applications.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98