Jet Global

MAY 1, 2020

Risk to the business. The mechanical solution is to build a data warehouse. The non-mechanical way to do it is to put a business sponsor on the team who believes in a transparent, fact-based approach to management. Data quality issues. Here’s the ugly truth: Everybody has a data quality problem.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

IBM Big Data Hub

OCTOBER 27, 2022

Yet Newcomp continues to be an essential and trusted partner, helping the company keep up with the high volume of analytics solutions it needs to address. Helping clients close the business analytics skills gap. The company’s up-to-date expertise with IBM Cognos Analytics and their close relationship with IBM are key factors.

Slice and Dice 52

Slice and Dice Analytics Sales Business Analytics 52

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. The platform comprises three powerful components: the watsonx.ai

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Poor data quality.

Big Data 52

Big Data Data Analytics Management Analytics 52

Jet Global

OCTOBER 1, 2019

Data Consolidation. A data warehouse can help you collect business data from multiple sources and use it for accurate reporting and analytics. BI powered by data warehouses can better correlate data from disparate systems and provide greater insight into the supply chain, sales, financials, etc.

Business Intelligence 40

Business Intelligence Forecasting Predictive Analytics Data Warehouse 40

Peter James Thomas

MAY 3, 2019

Control of Data to ensure it is Fit-for-Purpose. This refers to a wide range of activities from Data Governance to Data Management to Data Quality improvement and indeed related concepts such as Master Data Management. Data Architecture / Infrastructure. Best practice has evolved in this area.

Strategy 55

Strategy Data Architecture Data Strategy Data Quality 55

CIO Business Intelligence

APRIL 9, 2025

For many, the level of sophistication can easily range from more sophisticated solutions like Power BI, Tableau, SAP Analytics or IBM Cognos to mid-tier solutions like Domo, Qlik or the tried and true elder statesman for all business analytics consumers, Excel.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. This is where the observant reader will see the concept of Convergent Evolution playing out in the data arena as well as the Natural World. This is the essence of Convergent Evolution. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Domino Data Lab

JULY 22, 2019

The data governance, however, is still pretty much over on the data warehouse. Toward the end of the 2000s is when you first started getting teams and industry, as Josh Willis was showing really brilliantly last night, you first started getting some teams identified as “data science” teams. You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

datapine

AUGUST 29, 2022

Best for: the seasoned BI professional who is ready to think deep and hard about important issues in data analytics and big data. An excerpt from a rave review: “…a tour de force of the data warehouse and business intelligence landscape.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Jet Global

SEPTEMBER 26, 2023

Data Cleansing Imperative: The same report revealed that organizations recognized the importance of data quality, with 71% expressing concerns about data quality issues. This underscores the need for robust data cleansing solutions.

Data Quality 52

Data Quality Reporting Management Software 52

Jet Global

MARCH 13, 2024

Its easy-to-configure, pre-built templates get you up and running fast without having to understand complex Dynamics data structures. Free your team to explore data and create or modify reports on their own with no hard coding or programming skills required.

Reporting 52

Reporting Finance Data Quality Sales 52

Jet Global

FEBRUARY 23, 2024

A Centralized Hub for Data Data silos are the number one inhibitor to commerce success regardless of your business model. Through effective workflow, data quality, and governance tools, a PIM ensures that disparate content is transformed into a company-wide strategic asset.

Management 52

Management Sales Publishing Data Quality 52

Jet Global

JANUARY 13, 2023

Discover how SAP data quality can hurt your OTIF. If you deliver the right products on time, offering a regular price and good quality, you will have happy customers,” Richard den Ouden, co-founder of Angles of SAP. Live demo tailored to your business requirements. Interested in Business Analytics and Dashboards.

Measurement 52

Measurement Reporting Operational Reporting Forecasting 52

Jet Global

OCTOBER 4, 2023

Addressing these challenges often requires investing in data integration solutions or third-party data integration tools.

Finance 52

Finance Reporting Cost-Benefit Management 52

Jet Global

MARCH 4, 2024

Moving data across siloed systems is time-consuming and prone to errors, hurting data quality and reliability. Manual processes and juggling multiple tools won’t cut it under the ever-changing CSRD regulations. Inconsistent formats and standards across different tools further hinder comparison and aggregation.

Reporting 52

Reporting Data-driven Metrics Software 52

Andrew White

MARCH 22, 2019

This ties into the failure of data governance and MDM (see first item in this list). A data hub strategy should be economical, not perfected; and a data hub does not collect data like a data warehouses or data lake does – they are very different things. Age maybe against us.

Analytics 68

Analytics Metadata Data Governance Management 68

Jet Global

NOVEMBER 12, 2024

The majority, 62%, operate in a hybrid setting, which balances on-premises systems with cloud applications, making data integration even more convoluted.  Additionally, the need to synchronize data between legacy systems and the cloud ERP often results in increased manual processes and greater chances for errors.

Finance 52

Finance Reporting Cost-Benefit Data-driven 52