IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 66

Data Quality Data Integration Metadata Cost-Benefit 66

AWS Big Data

JULY 13, 2023

Target – Dashboards to be refreshed on a daily basis that would provide insights on sales, gross profit, sales pipelines, and customers. Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.

Optimization 92

Optimization B2B Data Quality Sales 92

DataKitchen

JUNE 19, 2023

Another way to look at the five pillars is to see them in the context of a typical complex data estate. Initially, the infrastructure is unstable, but then we look at our source data and find many problems. Our customers start looking at the data in dashboards and models and then find many issues. Was it on time?

Testing 130

Testing Cost-Benefit Metrics Data Quality 130

AWS Big Data

DECEMBER 21, 2023

Movement of data across data lakes, data warehouses, and purpose-built stores is achieved by extract, transform, and load (ETL) processes using data integration services such as AWS Glue. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 99

Analytics IT Data Lake Visualization 99

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. QuickSight offers scalable, serverless visualization capabilities.

Data Strategy 71

Data Strategy Strategy Data Warehouse Prescriptive Analytics 71

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

FineReport

APRIL 9, 2024

One of the key aspects of the role of BI platforms is their ability to streamline the process of data analysis and decision-making. They offer functionalities that allow for the integration and transformation of raw data into meaningful and actionable insights.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Andrew White

JUNE 11, 2019

Google acquires Looker – June 2019 (infrastructure/search/data broker vendor acquires analytics/BI). Salesforce closes acquisition of Mulesoft – May 2018 (business app vendor acquires data integration). There is also a lot of action in the data and analytics governance space for sure.

IT 82

IT Data Quality Data Integration Metadata 82

FineReport

JULY 18, 2022

The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization , such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than a pure programming tool. 15 Best Data Analysis Tools.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

Ontotext

JANUARY 6, 2022

That is why we have used GraphDB , Ontotext Platform and our significant expertise in semantic data integration to show how we can improve the quality of ENTSO-E Transparency data and develop flexible analytics by leveraging the knowledge graph approach. Spotting Data Consistency Issues. Let’s take a closer look.

Marketing 52

Marketing Data Quality Dashboards Visualization 52

FineReport

APRIL 26, 2023

” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards. The tool is designed to be intuitive, so even users with limited technical expertise can create reports and dashboards quickly and easily. Offers interactive and shared dashboards. Allows for batch processing.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. This provides a solid foundation for efficient data integration.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

AWS Big Data

APRIL 25, 2023

Looking for a tool that would enable us to democratize our data, we chose Amazon QuickSight , a cloud-native, serverless business intelligence (BI) service that powers interactive dashboards that lets us make better data-driven decisions, as a corporate solution for data visualization.

Visualization 52

Visualization IT Data-driven Reporting 52

Jet Global

MAY 1, 2020

We can almost guarantee you different results from each, and you end up with no data integrity whatsoever. Data quality issues. Here’s the ugly truth: Everybody has a data quality problem. This is because people won’t use BI applications that are founded on irrelevant, incomplete, or questionable data.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

AWS Big Data

JULY 12, 2023

A comprehensive testing framework ensures that your models consistently deliver accurate and reliable data, while modularity enables faster development via component reusability. Combined, these features can improve your data team’s velocity, ensure higher data quality, and empower team members to assume ownership.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

CIO Business Intelligence

FEBRUARY 20, 2023

To earn this cert, candidates should know how to maintain and modify Sales Cloud and Service Cloud applications; manage users, data, and security; and construct dashboards, reports, and workflows.

Consulting 60

Consulting B2B Cost-Benefit Sales 60

Howard Dresner

JANUARY 20, 2014

Examples: user empowerment and the speed of getting answers (not just reports) • There is a growing interest in data that tells stories; keep up with advances in storyboarding to package visual analytics that might fill some gaps in communication and collaboration • Monitor rumblings about trend to shift data to secure storage outside the U.S.

Business Intelligence 56

Business Intelligence Software Data Processing Marketing 56

DataKitchen

MAY 10, 2021

Data errors impact decision-making. When analytics and dashboards are inaccurate, business leaders may not be able to solve problems and pursue opportunities. Data errors infringe on work-life balance. Data errors also affect careers. You and your data team can accomplish the same thing at your organization.

Testing 214

Testing Manufacturing Data Quality Statistics 214

Peter James Thomas

SEPTEMBER 19, 2018

Data Classification. Data Consistency. Data Controls. Data Curation (contributor: Tenny Thomas Soman ). Data Democratisation. Data Dictionary. Data Engineering. Data Ethics. Data Integrity. Data Lineage. Data Platform. Data Strategy. Information Governance.

Analytics 45

Analytics Testing Data Strategy Data Integration 45

Andrew White

JANUARY 9, 2022

There are many tactics to employ that might help – including data literacy; storytelling; use of our value pyramid/business value model; use of our decision intelligence model. Link to item 6 on slide 27 is broken, [link] , for Dashboard to measure business impact, can you provide a current link? That is the key.

Analytics 64

Analytics Measurement Modeling Data-driven 64

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Quality 300

CIO Business Intelligence

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Data Architecture 100

Data Architecture Data Integration IoT Strategy 100

IBM Big Data Hub

JANUARY 17, 2023

This capability will provide data users with visibility into origin, transformations, and destination of data as it is used to build products. The result is more useful data for decision-making, less hassle and better compliance. Data integration. Start a trial.

Data-driven 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

Cloudera

SEPTEMBER 7, 2023

Perhaps the biggest challenge of all is that AI solutions—with their complex, opaque models, and their appetite for large, diverse, high-quality datasets—tend to complicate the oversight, management, and assurance processes integral to data management and governance. Systematize governance. Create core feedback mechanisms.

Insurance 79

Insurance Risk Data-driven Finance 79

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. These systems should collectively maintain data quality, integrity, and security, so the organization can use data effectively and efficiently. Why Is Data Governance in Healthcare Important?

Data Governance 52

Data Governance Measurement Metrics Modeling 52

datapine

FEBRUARY 22, 2022

IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

CIO Business Intelligence

NOVEMBER 7, 2023

“This has enabled every function to embrace data to make decisions, like which products to manufacture, how to price them, how much inventory to hold, and even predict when each device that we have deployed will break down,” Gupta says. Data Engineering, Data Governance, Data Integration, Data Management, Data Quality

Data Warehouse 139

Data Warehouse Digital Transformation Data-driven Reporting 139

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 1) Data Quality Management (DQM). We all gained access to the cloud.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

IBM Big Data Hub

AUGUST 4, 2023

When effectively implemented, a data democracy simplifies the data stack, eliminates data gatekeepers, and makes the company’s comprehensive data platform easily accessible by different teams via a user-friendly dashboard. By recognizing data as a product, it creates greater incentive to properly manage data.

Data Architecture 62

Data Architecture Data Lake Machine Learning Data Governance 62

datapine

MAY 17, 2021

If you have multiple databases from different touchpoints, you should look for a tool that will allow data integration no matter the amount of information you want to include. Besides connecting the data, the discovery tool you choose should also support working with big amounts of data. 7) Be easy to share.

Visualization 161

Visualization Data-driven Business Intelligence Metrics 161

Alation

JANUARY 27, 2022

Creating a single view of any data, however, requires the integration of data from disparate sources. Data integration is valuable for businesses of all sizes due to the many benefits of analyzing data from different sources. But data integration is not trivial. Establishes Trust in Data.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

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

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. Quickly and easily identify data quality or compatibility issues prior to migration for successful data cleanup and configuration.

Finance 52

Finance Reporting Data Integration Risk 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

MAY 9, 2024

Data pipelines play a critical role in modern data-driven organizations by enabling the seamless flow and transformation of substantial amounts of data across various systems and apps. The pipeline starts by extracting data from one or more sources, such as databases, files, APIs, or other data repositories.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52