Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

IT 317

IT Statistics KPI Data-driven 317

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Easy to report problems and receive updates on fixes.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

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.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

datapine

SEPTEMBER 27, 2022

A host of notable brands and retailers with colossal inventories and multiple site pages use SQL to enhance their site’s structure functionality and MySQL reporting processes. Whether you need to write database applications, perform administrative tasks or utilize a SQL report builder , this book is amongst the best books to learn SQL.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

datapine

MAY 21, 2019

In addition to increasing the price of deployment, setting up these data warehouses and processors also impacted expensive IT labor resources. The ROI alone from hours saved and reduced costs of producing current reports will improve your bottom line. 3) Analyzing data from different data sources.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards ROI 183

AWS Big Data

JANUARY 15, 2025

In the following section, two use cases demonstrate how the data mesh is established with Amazon DataZone to better facilitate machine learning for an IoT-based digital twin and BI dashboards and reporting using Tableau. In the past, one-to-one connections were established between Tableau and respective applications.

IoT 111

IoT Machine Learning Metadata Data-driven 111

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

Smart Data Collective

JULY 9, 2023

ETL is a three-step process that involves extracting data from various sources, transforming it into a consistent format, and loading it into a target database or data warehouse. Extract The extraction phase involves retrieving data from diverse sources such as databases, spreadsheets, APIs, or other systems.

Data Quality 105

Data Quality Data Warehouse Data-driven Reporting 105

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

Jet Global

JANUARY 20, 2021

As the volume of available information continues to grow, data management will become an increasingly important factor in effective business management. Lack of proactive data management, on the other hand, can result in incompatible or inconsistent sources of information, as well as data quality problems.

Data Analytics 95

Data Analytics Management Analytics Data Warehouse 95

AWS Big Data

SEPTEMBER 11, 2024

The application supports custom workflows to allow demand and supply planning teams to collaborate, plan, source, and fulfill customer orders, then track fulfillment metrics via persona-based operational and management reports and dashboards. The following diagram illustrates the solution architecture.

Data Architecture 111

Data Architecture Optimization Data Warehouse Metadata 111

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. Flat files – Other systems supply data in the form of flat files of different formats.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

AWS Big Data

FEBRUARY 27, 2024

Each data producer within the organization has its own data lake in Apache Hudi format, ensuring data sovereignty and autonomy. These datasets are pivotal for reporting and analytics use cases, powered by services like Amazon Redshift and tools like Power BI.

Data-driven 111

Data-driven Data Lake Data Quality Data Governance 111

AWS Big Data

DECEMBER 9, 2024

History management in data systems is fundamental for compliance, business intelligence, data quality, and time-based analysis. It enables organizations to maintain audit trails, perform trend analysis, identify data quality issues, and conduct point-in-time reporting.

Snapshot 64

Snapshot Data Warehouse Data Lake Data Quality 64

erwin

FEBRUARY 13, 2020

The 2020 State of Data Governance and Automation (DGA) shows that attitudes about data governance and the drivers behind it are changing – arguably for the better. Regulatory compliance was the biggest driver for data governance implementation, according to the 2018 report. Metadata Management Takes Time.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage).

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

datapine

FEBRUARY 22, 2022

Find out what is working, as you don’t want to totally scrap an already essential report or process. What data analysis questions are you unable to currently answer? This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Clean data in, clean analytics out.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 96

Analytics Data Warehouse Data Lake Metadata 96

CIO Business Intelligence

NOVEMBER 22, 2022

External data sharing gets strategic Data sharing between business partners is becoming far easier and much more cooperative, observes Mike Bechtel, chief futurist at business advisory firm Deloitte Consulting. CIOs should first understand the different approaches to observing data and how it differs from quality management,” he notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud.

Data Strategy 98

Data Strategy Strategy Data Warehouse Prescriptive Analytics 98

CIO Business Intelligence

MARCH 22, 2022

Consolidation creates a single source of truth on which to base decisions, actions, and reports. Which type(s) of storage consolidation you use depends on the data you generate and collect. . Another option is a data warehouse, which stores processed and refined data. Just starting out with analytics?

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

Smart Data Collective

OCTOBER 13, 2021

Data virtualization is ideal in any situation where the is necessary: Information coming from diverse data sources. Multi-channel publishing of data services. How does Data Virtualization manage data quality requirements? How does Data Virtualization complement Data Warehousing and SOA Architectures?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

CIO Business Intelligence

DECEMBER 21, 2022

BI software helps companies do just that by shepherding the right data into analytical reports and visualizations so that users can make informed decisions. Determining which BI delivery method fits best There are many traditional IT-managed ways to deliver reports and insights from data.

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

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

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders. Athena exposes the content of the reporting zone for consumption.

Optimization 98

Optimization B2B Data Quality Sales 98

CIO Business Intelligence

JANUARY 20, 2023

It’s About the Data For companies that have succeeded in an AI and analytics deployment, data availability is a key performance indicator, according to a Harvard Business Review report. [3] It provides rapid, direct access to trusted data for data scientists, business analysts, and others who need data to drive business value.

Analytics 137

Analytics Key Performance Indicator Unstructured Data Deep Learning 137

Jet Global

FEBRUARY 5, 2019

It’s hard to answer that question because, truth be told, you don’t know you’re using bad data until it’s too late. . states that about 40 percent of enterprise data is either inaccurate, incomplete, or unavailable. Because bad data is the reason behind poor analytics. . Top 5 Warning Signs of Bad Data. Ted Friedman.

Data Warehouse 69

Data Warehouse Data Quality Business Intelligence Data Governance 69

CIO Business Intelligence

JULY 28, 2023

At the same time, it reduces risk by ensuring that all data is under control, avoiding inconsistencies, and adhering to a single source of truth. In a recent IDC Infobrief , more than half of respondents report that regulatory compliance is a primary factor in deciding how and where they store enterprise data.

Risk 98

Risk Management Data mining Cost-Benefit 98

DataKitchen

JANUARY 19, 2022

DataKitchen acts as a process hub that unifies tools and pipelines across teams, tools and data centers. DataKitchen could, for example, provide the scaffolding upon which a Snowflake cloud data platform or data warehouse could be integrated into a heterogeneous data mesh domain.

Testing 130

Testing Data Integration Data Warehouse Enterprise 130

AWS Big Data

APRIL 4, 2024

Griffin is an open source data quality solution for big data, which supports both batch and streaming mode. In today’s data-driven landscape, where organizations deal with petabytes of data, the need for automated data validation frameworks has become increasingly critical.

Data Quality 86

Data Quality Data Lake Data Warehouse Data-driven 86

Octopai

JULY 12, 2020

After all, how do you adjust this month’s operations based on last month’s data if it takes two weeks to finally receive the information you need? This is exactly how Octopai customer, Farm Credit Services of America (FCSA) , felt when their BI team needed to modernize their data warehouse.

Data Warehouse 84

Data Warehouse Data Quality Metadata Risk Management 84

Jet Global

JULY 11, 2019

In order to understand demand and accurately predict supply, most companies adopt a business intelligence solution to assist with data preparation, data consolidation, analysis, and reporting. BI software is built to collect, unify, sort, tag, analyze, and report on vast amounts of data. Data Consolidation.

Business Intelligence 72

Business Intelligence Forecasting Predictive Analytics Data Warehouse 72