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 Digital Transformation 105

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 117

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 117

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

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

Sisense

OCTOBER 6, 2020

These programs and systems are great at generating basic visualizations like graphs and charts from static data. The challenge comes when the data becomes huge and fast-changing. Why is quantitative data important? Qualitative data benefits: Unlocking understanding. Qualitative data can go where quantitative data can’t.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

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.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

SEPTEMBER 21, 2023

Enterprises still aren’t extracting enough value from unstructured data hidden away in documents, though, says Nick Kramer, VP for applied solutions at management consultancy SSA & Company. Data warehouses then evolved into data lakes, and then data fabrics and other enterprise-wide data architectures.

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 114

Data Lake Metadata Optimization Statistics 114

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

CIO Business Intelligence

JUNE 29, 2022

If you’re used to using SQL Server Analysis Services for business intelligence, Analysis Services offers that enterprise-grade analytics engine as a cloud service that you can also connect to Power BI. Azure Data Factory. Azure Data Lake Analytics. Microsoft. Azure Analysis Services.

Data Lake 115

Data Lake Analytics Data Warehouse Machine Learning 115

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

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. Meet the data lakehouse.

Data Lake 111

Data Lake Unstructured Data Data Warehouse Data Quality 111

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

CIO Business Intelligence

APRIL 4, 2023

Let’s look at the data architecture journey to understand why and how data lakehouses help to solve complexity, value and security. Traditionally, data warehouses have stored curated, structured data to support analytics and business intelligence, with fast, easy access to data.

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

CIO Business Intelligence

MAY 24, 2022

The survey found the mean number of data sources per organisation to be 400, and more than 20 percent of companies surveyed to be drawing from 1,000 or more data sources to feed business intelligence and analytics systems. Today transactional data is the largest segment, which includes streaming and data flows.

Data-driven 90

Data-driven Data Lake Data Warehouse Cost-Benefit 90

BizAcuity

MAY 10, 2022

2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence. Fact: IBM built the world’s first data warehouse in the 1980’s. Microsoft also releases Power BI, a data visualization and business intelligence tool. who saw the potential that cloud offered.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

BizAcuity

APRIL 14, 2022

The best way to avoid poor data quality is having a strict data governance system in place. The majority of the data a business has stored is generally unstructured. Most of these are accumulated in data silos or data lakes. Unstructured Data Management. Slow query performance.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 64

Data Warehouse Data Lake Cost-Benefit Modeling 64

Sisense

MAY 28, 2019

Every decade, like clockwork, the Business Intelligence (BI) industry welcomes the next generation of BI platform providers. 2019 can best be described as an era of modern cloud data analytics. Two orthogonal approaches to data analytics have developed in this decade of BI: 1. The truth always rises to the surface.

Data Analytics 89

Data Analytics Data Lake Analytics Unstructured Data 89

Cloudera

MAY 16, 2018

This example combines three types of unrelated data: Legal entity data: Two companies with completely unrelated business lines (coffee and waste management) merged together; Unstructured data: Fraudulent promotion campaigns took place through press releases and a fake stock-picking robot.

Data Lake 41

Data Lake Risk Visualization Unstructured Data 41

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 75

Data Quality Testing Data Warehouse Unstructured Data 75

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

AWS Big Data

JULY 28, 2023

Amazon Redshift is a petabyte-scale, enterprise-grade cloud data warehouse service delivering the best price-performance. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools.

Data Lake 66

Data Lake Data Governance Data Warehouse Modeling 66

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. 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

Jet Global

NOVEMBER 21, 2023

To have any hope of generating value from growing data sets, enterprise organizations must turn to the latest technology. You’ve heard of data warehouses, and probable data lakes, but now, the data lakehouse is emerging as the new corporate buzzword. To address this, the data lakehouse was born.

Data Lake 52

Data Lake Data Warehouse Reporting Enterprise 52