erwin

APRIL 29, 2020

Without data lineage, these functions are irrelevant, so it makes sense for a business to have a clear understanding of where data comes from, who uses it, and how it transforms. Business terms and data policies should be implemented through standardized and documented business rules. See: The Benefits of Data Governance.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

Sisense

OCTOBER 15, 2020

Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. Streaming data analytics is expected to grow into a $38.6 Every data professional knows that ensuring data quality is vital to producing usable query results.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

Jet Global

MARCH 13, 2024

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting.

Reporting 52

Reporting Finance Data Quality Sales 52

AWS Big Data

MARCH 3, 2023

For users that require a unified view of software quality, this is unacceptable. In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. Overall, DataOps is an essential component of modern data-driven organizations. Query> DataOps.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Jet Global

AUGUST 24, 2023

It streamlines data integration, ensures real-time access to accurate information, enhances collaboration, and provides the flexibility needed to adapt to evolving ERP systems and business requirements. Data transformation ensures that the data aligns with the requirements of the new cloud ERP system. Privacy Policy.

Finance 52

Finance Reporting Data Integration Risk 52

Jet Global

MAY 28, 2019

A database is, by definition, ‘any collection of data organized for storage, accessibility, and retrieval.’ Databases usually consist of information arranged in rows, columns, and tables, organized mainly for easy input and collection of different events. while rows will contain the individual events and trades themselves.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

CIO Business Intelligence

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 127

Analytics Machine Learning Software Data Quality 127

Peter James Thomas

OCTOBER 30, 2018

It may well be that one thing that a CDO needs to get going is a data transformation programme. This may purely be focused on cultural aspects of how an organisation records, shares and otherwise uses data. It may be to build a new (or a first) Data Architecture. It may be to build a new (or a first) Data Architecture.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

Alation

OCTOBER 28, 2021

Data & analytics represents a major opportunity to tackle these challenges. Indeed, many healthcare organizations today are embracing digital transformation and using data to enhance operations. To make good on this potential, healthcare organizations need to understand their data and how they can use it.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making.

Visualization 136

Visualization Cost-Benefit Big Data Prescriptive Analytics 136