Octopai

MAY 31, 2022

If your data management enables you to breathe a sigh of relief (as opposed to jumping for joy), that’s a good sign that it’s managing data as a liability. In contrast, data management for BI is asset management. Business intelligence is the primary place where your data becomes an asset.

Management 52

Management Metadata Business Intelligence ROI 52

CIO Business Intelligence

NOVEMBER 22, 2022

“Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.” The next step in every organization’s data strategy, Guan says, should be investing in and leveraging artificial intelligence and machine learning to unlock more value out of their data.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 86

Strategy Data Architecture Cost-Benefit Reporting 86

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Unlike ingestion processes, data can be transformed as per business rules before loading.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

CIO Business Intelligence

APRIL 29, 2022

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. Further, data management activities don’t end once the AI model has been developed. era is upon us.

Data Governance 142

Data Governance IT Risk Data Lake 142

CIO Business Intelligence

MARCH 29, 2022

It isn’t practical to save all your data, but it is important to realize data may be valuable for other projects. You lose that add-on value when you throw data away. . This type of data waste results in missing out on the second project advantage. You have data but don’t use it.

Cost-Benefit 52

Cost-Benefit Machine Learning Metadata Data Quality 52

Cloudera

AUGUST 31, 2021

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis. Consideration of both data & metadata in the migration.

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

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. Data quality Data quality is essentially the measure of data integrity.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

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

Jet Global

JULY 2, 2019

And using Azure’s built-in U-SQL library allows businesses allows you to write code once and have it automatically parallelized for the scale you need, whether in.NET languages, R, or Python. At the very worst, data lakes can provide a wealth of data that is impossible to analyze in a meaningful way due to incorrect metadata or cataloging.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. Without proper quality control, data inaccuracies are more likely to occur.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

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

AWS Big Data

MAY 7, 2024

Figure 1: Flow of actions for self-service analytics around data assets stored in relational databases First, the data producer needs to capture and catalog the technical metadata of the data asset. The producer also needs to manage and publish the data asset so it’s discoverable throughout the organization.

Metadata 75

Metadata Data Lake Data Processing Data-driven 75

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Peter James Thomas

AUGUST 18, 2018

Next, rather than just being the province of Data Scientists, there were moves to use Data Lakes to support general Data Discovery and even business Reporting and Analytics as well. This required additional investments in metadata.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 126

IT Business Intelligence Sales Key Performance Indicator 126

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Forrester ).

Data Architecture 79

Data Architecture Data Lake Metadata Data Warehouse 79

CIO Business Intelligence

JUNE 12, 2024

Some of the models are traditional machine learning (ML), and some, LaRovere says, are gen AI, including the new multi-modal advances. The generative AI is filling in data gaps,” she says. This was not accessible in the past without complex, custom solutions that were often very brittle.”

Modeling 132

Modeling Testing Cost-Benefit IT 132

Alation

OCTOBER 21, 2021

Data lakes also support the growing thirst for analysis by data scientists and data analysts, as well as the critical role of data governance. But setting up a data lake takes a thoughtful approach to ensure it’s positioned to prevent it from becoming a data swamp. Lack of metadata. Ungoverned data.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 99

Data Lake Unstructured Data Data Warehouse Data Quality 99

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 76

Cost-Benefit Metadata Optimization Management 76

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale.

Data Lake 87

Data Lake Analytics Snapshot Optimization 87

Alation

MARCH 21, 2023

When it embarked on a digital transformation and modernization initiative in 2018, the company migrated all its data to AWS S3 Data Lake and Snowflake Data Cloud to provide accessibility to data to all users. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

datapine

JANUARY 31, 2022

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. Experience the power of Business Intelligence with our 14-days free trial! Why Is Business Intelligence So Important?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. It also helps capture and connect data based on business or domains.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

Alation

DECEMBER 15, 2021

This includes where the organization stores, processes, and transmits it (details an organization must be ready to share with auditors, or increasingly, with individuals whose personal data has been captured and seek to have a say in how companies use it.). At the same time, it enhances data security and compliance programs.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

AWS Big Data

MAY 1, 2024

Solution overview OneData defines three personas: Publisher – This role includes the organizational and management team of systems that serve as data sources. Responsibilities include: Load raw data from the data source system at the appropriate frequency. Provide and keep up to date with technical metadata for loaded data.

Dashboards 111

Dashboards Publishing Data-driven Cost-Benefit 111

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. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Alation

AUGUST 26, 2021

What Is Data Intelligence? Data intelligence is a system to deliver trustworthy, reliable data. It includes intelligence about data, or metadata. IDC coined the term, stating, “data intelligence helps organizations answer six fundamental questions about data.”

Metadata 64

Metadata Data Governance Dashboards Software 64

BI-Survey

FEBRUARY 6, 2020

Today’s data-literate users want governed and scalable self-service BI functions to answer critical business questions and to get the most out of their data assets. Most prominently, machine learning (ML) enables improvements in various fields. Data management has always been a challenge for companies.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

AWS Big Data

JUNE 14, 2023

We were frustrated by the limitations of our previous business intelligence (BI) solution, which was holding us back from our vision to accelerate data sharing, team collaboration, and security within Amazon. Reusable – The ultimate goal of FAIRS is to optimize the reuse of data.

Dashboards 76

Dashboards KPI Scorecard Metadata 76

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52