AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 95

Data Warehouse Data-driven Machine Learning B2B 95

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 90

Data Lake Data Warehouse Machine Learning Cost-Benefit 90

AWS Big Data

AUGUST 7, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Solution overview Amazon Forecast is a fully managed time series forecasting service based on machine learning.

Forecasting 85

Forecasting Data Warehouse Machine Learning Modeling 85

Sisense

JANUARY 1, 2020

Data and analytics are all about finding patterns, figuring out what’s next, and creating a better world. In Build the Future of Data , we give you insights into the tools and trends that will define the next era of business. Few worlds have a pace of innovation quite like data and analytics. Read on to learn more.

Analytics 98

Analytics Digital Transformation Data Warehouse Dashboards 98

Cloudera

JULY 15, 2019

At a time when machine learning, deep learning, and artificial intelligence capture an outsize share of media attention, jobs requiring SQL skills continue to vastly outnumber jobs requiring those more advanced skills. Educating Data Analysts at Scale. What We Teach. How to Enroll.

Big Data 56

Big Data Deep Learning Data Warehouse Data-driven 56

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Digital Transformation 105

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 105

Jen Stirrup

MAY 3, 2020

Azure Synapse is an Azure-based cloud analytics service that provides insights on all data across data warehouses and big data analytics systems. It combines familiar SQL technologies such as data warehousing with Spark technologies used in big data analytics. Azure Synapse docs on GitHub.

Big Data 57

Big Data Data Warehouse Machine Learning Business Intelligence 57

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

Cloudera

FEBRUARY 7, 2019

Enabling this transformation is the HDP platform, along with SAS Viya on Google Cloud , which has delivered machine learning models and personalization at scale. This has become a core component of the fraud management framework for the business, and has helped solidify its role as the trusted keeper of sensitive data.

Big Data 64

Big Data Data Analytics Analytics Data Architecture 64

AWS Big Data

OCTOBER 20, 2023

Regarding the Azure Data Lake Storage Gen2 Connector, we highlight any major differences in this post. AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning, and application development.

Data Lake 86

Data Lake Big Data Consulting Data Warehouse 86

CIO Business Intelligence

FEBRUARY 14, 2023

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. report they have established a data culture 26.5% report they have a data-driven organization 39.7%

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

IBM Big Data Hub

OCTOBER 30, 2023

Thus, DB2 PureScale on AWS equips this insurance company to innovate and make data-driven decisions rapidly, maintaining a competitive edge in a saturated market. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

Insurance 84

Insurance Data Warehouse Data-driven Unstructured Data 84

Laminar Security

DECEMBER 13, 2023

They offer a comprehensive solution to enhance your cloud security posture and effectively manage your data. The primary focus of discovery is to find all the places where data exists and identify the assets it resides in. Data discovery and classification play a pivotal role in decision-making processes within organizations.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

erwin

AUGUST 15, 2022

This blog is based upon a recent webcast that can be viewed here. For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. Moreover, this blog will provide readers with a firm foundation for NoSQL and data lakes as they move to the cloud.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

Cloudera

JANUARY 26, 2022

The amount of data being collected grew, and the first data warehouses were developed. Big Data” became a topic of conversations and the term “Cloud” was coined. . The post 96 Percent of Businesses Can’t Be Wrong: How Hybrid Cloud Came to Dominate the Data Sector appeared first on Cloudera Blog.

Data Processing 83

Data Processing IoT Cost-Benefit Digital Transformation 83

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The first diagram illustrates the architecture before using data sharing.

Testing 101

Testing Data Warehouse Metrics Cost-Benefit 101

IBM Big Data Hub

APRIL 28, 2022

Problem : Traditionally, developing a solid backorder forecast model that takes every factor into consideration would take anywhere from weeks to months as sales data, inventory or lead-time data and supplier data would all reside in disparate data warehouses.

Metadata 84

Metadata Data Warehouse Forecasting Predictive Modeling 84

Cloudera

JULY 14, 2023

Introduction For more than a decade now, the Hive table format has been a ubiquitous presence in the big data ecosystem, managing petabytes of data with remarkable efficiency and scale. Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration.

Snapshot 69

Snapshot Metadata Data Warehouse Testing 69

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). Enable responsible, transparent and explainable data and AI workflows with watsonx.governance.

Risk 76

Risk Modeling Management Metadata 76

AWS Big Data

JUNE 23, 2023

This blog post is co-written with Ori Nakar from Imperva. Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. SPICE provides consistently fast query performance and automatically scales for high concurrency.

Data Lake 69

Data Lake Cost-Benefit Dashboards Data Warehouse 69

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. Summary AWS Data Quality is now Generally Available.

Data Quality 95

Data Quality Statistics Data Lake Visualization 95

Alation

JULY 30, 2021

A part of that journey often involves moving fragmented on-premises data to a cloud data warehouse. You clearly shouldn’t move everything from your on-premises data warehouses. Otherwise, you can end up with a data swamp. Put differently, you can migrate faster if you know the right data to move.

Data Warehouse 52

Data Warehouse Data Governance Machine Learning Data-driven 52

Sisense

JANUARY 13, 2020

In Moving Parts , we explore the unique data and analytics challenges manufacturing companies face every day. The world of data in modern manufacturing. From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. How data enhances product development.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

Cloudera

OCTOBER 23, 2017

Your enterprise big data and machine learning initiatives can be delayed, fail, or risk security breach unless you choose the most mature, most tightly integrated platform. More information on SDX is in our engineering blog. Check it out! The post Cloudera CDH 5.13

Machine Learning 40

Machine Learning Big Data Risk Data Science 40

Sisense

APRIL 26, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. Structured vs unstructured data.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

IBM Big Data Hub

NOVEMBER 15, 2023

Watsonx gives organizations the ability to refine foundation models with their own domain-specific data to gain competitive advantage and ensure factual grounding to external sources of knowledge. Thus, teams can work smarter and move toward better, more integrated business outcomes.

Sales 92

Sales Software Modeling Enterprise 92

datapine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. While analysts focus on historical data to understand current business performance, scientists focus more on data modeling and prescriptive analysis. Business Intelligence Job Roles. And it’s completely free!

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. To solve practical decision problems, the Data Scientist typically uses combinations of these methods.

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

BizAcuity

MAY 16, 2022

To stay relevant in the market and to increase brand awareness, organizations use big data analytics and business intelligence to navigate their way after getting a full understanding of their ideal customers and their behavior before and during the buying journey. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Cloudera

SEPTEMBER 12, 2018

It’s a big week for us, as many Clouderans descend on New York for the Strata Data Conference. The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Enterprise Machine Learning: .

Machine Learning 44

Machine Learning Big Data Data Science Data Warehouse 44

IBM Big Data Hub

JULY 5, 2022

Nedbank builds a scalable data warehouse architecture . Endless data but your queries aren’t fast enough. Empower real-time decision making and perform heavy computational analysis with built-in ML, insanely fast ingest, and querying of data in motion and at rest. Exxon transforms customer experiences .

Data Lake 94

Data Lake Data Warehouse Publishing Structured Data 94

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. In this blog, we share our takeaways as they relate to the DMSA market trends. Cloudera’s Positioning. Cloudera is positioned furthest for “Completeness of Vision.”

Management 42

Management Metadata Analytics Machine Learning 42

Alation

FEBRUARY 13, 2020

This brief definition makes several points about data catalogs—data management, searching, data inventory, and data evaluation—but all depend on the central capability to provide a collection of metadata. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

IBM Big Data Hub

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. This blog post provides a concise session summary, a video, and a written transcript. data science’s emergence as an interdisciplinary field – from industry, not academia. But for most enterprise, using machine learning…not really.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

AWS Big Data

APRIL 20, 2023

Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 78

Data Lake Data Warehouse Sales Data-driven 78