CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 134

Analytics Data Science Unstructured Data Data mining 134

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Big data and data warehousing.

Technology 134

Technology Data Warehouse Big Data Machine Learning 134

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

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

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. Data ingestion/integration services. Data orchestration tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

CIO Business Intelligence

SEPTEMBER 22, 2023

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 103

Management Advertising Data Lake Sales 103

Cloudera

OCTOBER 11, 2022

This leads to the obvious question – how do you do data at scale ? Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. The challenge for AI is how to do data in all its complexity – volume, variety, velocity.

Snapshot 92

Snapshot Data Science Digital Transformation Metadata 92

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 126

Analytics Data Science Statistics Unstructured Data 126

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ). Gartner ).

Data Architecture 78

Data Architecture Data Lake Metadata Data Warehouse 78

DataRobot Blog

MARCH 8, 2023

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

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 67

Data Warehouse Data Lake Cost-Benefit Modeling 67

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 143

Management Advertising Data Lake Sales 143

datapine

AUGUST 29, 2022

Best for : the new intern who has no idea what data science even means. An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Cloudera Data Warehouse (CDW) is here to save the day! CDW is an integrated data warehouse service within Cloudera Data Platform (CDP).

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

CIO Business Intelligence

JANUARY 20, 2023

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Intelligence 143

Business Intelligence Dashboards Data mining OLAP 143

Cloudera

JUNE 2, 2022

This blog aims to answer two questions: What is a universal data distribution service? Why does every organization need it when using a modern data stack? Use cases demand that data no longer be distributed to just a data warehouse or subset of data sources, but to a diverse set of hybrid services across cloud providers and on-prem.

Enterprise 102

Enterprise Data Lake Data Collection Data-driven 102

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. Data collection and management shouldn’t be classified as just another project, Gusher notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

JULY 13, 2022

This blog aims to answer two questions: What is a universal data distribution service? Why does every organization need it when using a modern data stack? Use cases demand that data no longer be distributed to just a data warehouse or subset of data sources, but to a diverse set of hybrid services across cloud providers and on-prem.

Enterprise 65

Enterprise Data Lake Data Collection Data-driven 65

Cloudera

FEBRUARY 16, 2022

Each project consists of a declarative series of steps or operations that define the data science workflow. We can think of model lineage as the specific combination of data and transformations on that data that create a model. Each user associated with a project performs work via a session.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

Jet Global

AUGUST 14, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. This also helps business functions avoid unnecessary data logjams and giving them instant access they need to the data they so desperately require.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Cloudera

JANUARY 11, 2018

Data science and advanced analytics deliver more value if organizations can deploy models and algorithms on detailed data brought together from many sources, not just on summaries or samples contained in a single data warehouse or data mart.” ” And teases at the reward.

Strategy 40

Strategy Data Warehouse Cost-Benefit Marketing 40

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Jet Global

OCTOBER 2, 2019

And how can the data collected across multiple touchpoints, from retail locations to the supply chain to the factory be easily integrated? Enter data warehousing. This also helps business functions avoid unnecessary data logjams and giving them instant access they need to the data they so desperately require.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Birst BI

JUNE 18, 2018

Read Gartner’s latest research, “Doing Machine Learning Without Hiring (More) Data Scientists,” which carves out four recommendations for organizations wishing to launch data science initiatives. We rely on data and analytics to assist in all three areas.

Slice and Dice 76

Slice and Dice Machine Learning Sales Data-driven 76

Data Virtualization

DECEMBER 22, 2022

Reading Time: 3 minutes We are naturally inclined to think that our relationship with data develops solely in the world > data > use direction, in which data captures what happens in the world, and we use data to understand events in the world.

Data Integration 52

Data Integration Management Data Warehouse Data Collection 52