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

CIO Business Intelligence

FEBRUARY 16, 2023

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

Smart Data Collective

OCTOBER 13, 2021

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement. How does Data Virtualization manage data quality requirements?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

CIO Business Intelligence

JANUARY 20, 2023

Storing the data : Many organizations have plenty of data to glean actionable insights from, but they need a secure and flexible place to store it. The most innovative unstructured data storage solutions are flexible and designed to be reliable at any scale without sacrificing performance.

Analytics 137

Analytics Key Performance Indicator Unstructured Data Deep Learning 137

Smart Data Collective

SEPTEMBER 26, 2021

Data mining and knowledge go hand in hand, providing insightful information to create applications that can make predictions, identify patterns, and, last but not least, facilitate decision-making. Working with massive structured and unstructured data sets can turn out to be complicated. If it’s not done right away, then later.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

datapine

FEBRUARY 22, 2022

This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

Octopai

MARCH 22, 2023

Data migration can be a daunting task, especially when dealing with large volumes of data. Snowflake is one of the leading cloud-based data warehouse that provides scalability, flexibility, and ease of use. Snowflake data warehouse platform has been designed to leverage the power of modern-day cloud computing technology.

Cost-Benefit 103

Cost-Benefit Data Warehouse Unstructured Data Optimization 103

CIO Business Intelligence

AUGUST 9, 2022

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Alation

AUGUST 4, 2022

A key challenge of legacy approaches involved data quality. How could you ensure data was valid and accurate, and then follow through on new insights with action? It got people realizing that data is a business tool, and that technologists are the custodians of that data,” points out New Zealand CIO Anthony McMahon.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

CIO Business Intelligence

OCTOBER 2, 2024

Collect, filter, and categorize data The first is a series of processes — collecting, filtering, and categorizing data — that may take several months for KM or RAG models. Structured data is relatively easy, but the unstructured data, while much more difficult to categorize, is the most valuable.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 98

Data Quality Testing Data Warehouse Unstructured Data 98

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

Cloudera

SEPTEMBER 9, 2022

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Metadata 102

Metadata Machine Learning Unstructured Data Data Lake 102

CDW Research Hub

SEPTEMBER 15, 2020

Business leaders need to be able to quickly access data—and to trust the accuracy of that data—to make better decisions. Traditional data warehouses are often too slow and can’t handle large volumes of data or different types of semi-structured or unstructured data.

Business Intelligence 52

Business Intelligence Prescriptive Analytics Unstructured Data Data Warehouse 52

Jedox

OCTOBER 22, 2020

Gartner defines “dark data” as the data organizations collect, process, and store during regular business activities, but doesn’t use any further. Gartner also estimates 80% of all data is “dark”, while 93% of unstructured data is “dark.”.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

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 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Wayne Yaddow

MARCH 14, 2025

The early detection and prevention method is essential for businesses where data accuracy is vital, including banking, healthcare, and compliance-oriented sectors. dbt Cloud vs. dbt Core: Data Transformations TestingFeatures dbt Cloud and dbt Core Data TestingFeatures Some Testing Features Missing From dbt Core: How ToMitigate 1.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The many data warehouse systems designed in the last 30 years present significant difficulties in that respect.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Ensuring data quality is made easier as a result.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Hurwitz & Associates

JULY 10, 2018

The volume and even types of data relevant to doing business have been growing at an accelerated pace for some time, in great part as an outgrowth of web-based applications designed to reach consumers and support end user activities such as social media. The amounts of data a highly scaled IoT environment represents raise the stakes here.

IoT 40

IoT Management Internet of Things Unstructured Data 40

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

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. Consolidating all data across your organization builds trust in the data.

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52

CIO Business Intelligence

APRIL 9, 2025

Revisiting the foundation: Data trust and governance in enterprise analytics Despite broad adoption of analytics tools, the impact of these platforms remains tied to data quality and governance. This capability has become increasingly more critical as organizations incorporate more unstructured data into their data warehouses.

Enterprise 102

Enterprise Analytics Experimentation Machine Learning 102

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

BI-Survey

MARCH 6, 2025

For data management teams, achieving more with fewer resources has become a familiar challenge. While efficiency is a priority, data quality and security remain non-negotiable. Developing and maintaining data transformation pipelines are among the first tasks to be targeted for automation.

Data Warehouse 52

Data Warehouse Metadata Unstructured Data Data-driven 52

CIO Business Intelligence

MARCH 26, 2025

New technology became available that allowed organizations to start changing their data infrastructures and practices to accommodate growing needs for large structured and unstructured data sets to power analytics and machine learning.

Data Quality 129

Data Quality Forecasting Unstructured Data Data-driven 129