IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 100

Data Lake Sales Data Warehouse Snapshot 100

Data Science 101

NOVEMBER 11, 2019

Welcome to the first beta edition of Cloud Data Science News. This will cover major announcements and news for doing data science in the cloud. Azure Synapse Analytics This is the future of data warehousing. Azure Synapse Analytics This is the future of data warehousing. Microsoft Azure. Google Cloud.

Data Science 95

Data Science Machine Learning Data Lake Visualization 95

KDnuggets

DECEMBER 14, 2021

We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.

Data Science 159

Data Science Machine Learning Analytics Data Lake 159

Sisense

DECEMBER 23, 2019

Artificial Intelligence and machine learning are the future of every industry, especially data and analytics. Let’s talk about AI and machine learning (ML). AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

Machine Learning 84

Machine Learning Modeling Metadata Recreation/Entertainment 84

Data Science 101

NOVEMBER 7, 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. R Support for Azure Machine Learning. Azure Synapse.

Data Science 106

Data Science Machine Learning Data Lake IoT 106

Data Science 101

DECEMBER 16, 2019

Even though Amazon is taking a break from announcements (probably focusing on Christmas shoppers), there are still some updates in the cloud data science world. Azure Tips and Tricks: Make your data Searchable A quick video to demonstrate Azure Search. Courses and Learning. Here they are. Signup for the Newsletter.

Data Science 81

Data Science Metadata Machine Learning Data Lake 81

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

CIO Business Intelligence

MARCH 9, 2022

Despite the worldwide chaos, UAE national airline Etihad has managed to generate productivity gains and cost savings from insights using data science. Etihad began its data science journey with the Cloudera Data Platform and moved its data to the cloud to set up a data lake. Reem Alaya Lebhar.

Data Science 98

Data Science Data Lake Cost-Benefit Digital Transformation 98

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 93

Data Lake Data Warehouse Machine Learning Cost-Benefit 93

David Menninger's Analyst Perspectives

JANUARY 14, 2021

Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs. But unlocking value from data requires multiple analytics workloads, data science tools and machine learning algorithms to run against the same diverse data sets.

Machine Learning 227

Machine Learning Data Governance Big Data Data Science 227

Cloudera

JULY 18, 2018

Additionally, organizations are increasingly restrained due to budgetary constraints and having limited data sciences resources. It is fair to say that healthcare faces many challenges, including developing, deploying, and integrating machine learning and artificial intelligence (AI) into clinical workflow and care delivery.

Machine Learning 50

Machine Learning Predictive Analytics Analytics Prescriptive Analytics 50

CIO Business Intelligence

MAY 24, 2022

The new, industry-targeted data management platforms — Intelligent Data Management Cloud for Health and Life Sciences and the Intelligent Data Management Cloud for Financial Services — were announced at the company’s Informatica World conference Tuesday. Intelligent Data Management Cloud for Health and Life Sciences.

Finance 140

Finance Management Metadata Data Quality 140

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

CIO Business Intelligence

APRIL 25, 2022

“You can think that the general-purpose version of the Databricks Lakehouse as giving the organization 80% of what it needs to get to the productive use of its data to drive business insights and data science specific to the business. Features focus on media and entertainment firms.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. On premises or in SAP cloud. Per user, per month.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

Boris Evelson

JUNE 14, 2023

No matter what technology foundation you’re using – a data lake, a data warehouse, data fabric, data mesh, etc. – BI applications are where business users consume data and turn it into actionable insights and decisions. The BI market has […]

Business Intelligence 98

Business Intelligence Data Lake Data Warehouse Data-driven 98

Cloudera

AUGUST 18, 2021

Data Lifecycle Management: The Key to AI-Driven Innovation. In digital transformation projects, it’s easy to imagine the benefits of cloud, hybrid, artificial intelligence (AI), and machine learning (ML) models. The hard part is to turn aspiration into reality by creating an organization that is truly data-driven.

Data Lake 88

Data Lake IoT Internet of Things Data-driven 88

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Data Virtualization

JANUARY 19, 2023

Reading Time: 2 minutes Today, many businesses are modernizing their on-premises data warehouses or cloud-based data lakes using Microsoft Azure Synapse Analytics. Unfortunately, with data spread.

Data Analytics 52

Data Analytics Data Lake Data Warehouse Analytics 52

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. INDUSTRY TRANSFORMATION. Last, but certainly not least.

Digital Transformation 69

Digital Transformation Machine Learning Optimization Data Lake 69

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. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

CIO Business Intelligence

OCTOBER 1, 2022

P&G is also piloting the use of IIoT, advanced algorithms, machine learning (ML), and predictive analytics to improve manufacturing efficiencies in the production of paper towels. This, in turn, improves cycle time, reduces network losses, and ensures quality, all while improving operator productivity.

Manufacturing 145

Manufacturing Digital Transformation IoT Internet of Things 145

CIO Business Intelligence

MARCH 27, 2024

Nella Pubblica amministrazione c’è un ulteriore parametro che entra nella data governance: la maturità sugli open data. “Al Al momento stiamo sperimentando la nuova data platform per un numero selezionato di applicazioni mission-critical, come il processo di autoliquidazione. Ma ci aspettiamo di estenderla ad altri use-case”.

Data Governance 52

Data Governance Data Lake Data Strategy Data-driven 52

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects. Data Ingestion.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). It can be used with both on-premise and multi-cloud environments.

Risk 70

Risk Modeling Management Metadata 70

Cloudera

JANUARY 24, 2022

The company used Cloudera Data Science Workbench to create data-centric applications and solutions. Working with Cloudera, Keck created a data lake that eliminated manual data collection errors and gave visibility organization-wide. Winner of the Data Impact Awards 2021: Data for Good.

Data Lake 64

Data Lake Risk Machine Learning Data Collection 64

FineReport

MARCH 24, 2024

Each language serves distinct purposes, from performance-oriented applications to web development and data science. Data Analyst Job Description: Data Analysis Tools Data analysts rely on an array of tools to collect and interpret data effectively.

Statistics 52

Statistics Data mining Visualization Reporting 52

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

FEBRUARY 13, 2020

Just as you need data about finances for effective financial management, you need data about data (metadata) for effective data management. You can’t manage data without metadata. Data catalogs change the game and elevate best practices for metadata management with: Crowdsourced metadata.

Metadata 52

Metadata Management Data Lake Data Governance 52

AWS Big Data

JUNE 20, 2023

It manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Data labeling is required for various use cases, including forecasting, computer vision, natural language processing, and speech recognition.

Data Lake 71

Data Lake Data Science Recreation/Entertainment Experimentation 71

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Machine Learning Workspace exists . A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

CIO Business Intelligence

SEPTEMBER 21, 2023

“We’re still in the early phases of this,” says Donncha Carroll, partner in the revenue growth practice and head of the data science team at Lotis Blue Consulting. Many data science tools and base models are open source, or are based heavily on open-source projects. Artificial Intelligence, Machine Learning

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

Cloudera

DECEMBER 8, 2020

You can read it online here: Federated Learning. Federated Learning is a paradigm in which machine learning models are trained on decentralized data. First, it makes data privacy easier. Since the data is never transferred to a central location, the data cannot be aggregated or combined with other data.

Machine Learning 85

Machine Learning Data Lake Reporting Modeling 85

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52