Cloudera

FEBRUARY 8, 2021

Predictive Analytics – predictive analytics based upon AI and machine learning (predictive maintenance, demand-based inventory optimization as examples). Security & Governance – an integrated set of security, management and governance technologies across the entire data lifecycle.

Manufacturing 118

Manufacturing Data Warehouse Sales Predictive Analytics 118

CIO Business Intelligence

SEPTEMBER 12, 2022

Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases. Fazal instructed his IT team to collect every bit of data and methodically determine its use later, rather than lose “precious” data in the rush to build a massive data warehouse. “We

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

David Menninger's Analyst Perspectives

SEPTEMBER 19, 2024

Snowflake was founded in 2012 to build a business around its cloud-based data warehouse with built-in data-sharing capabilities. Snowflake has expanded its reach over the years to address data engineering and data science, and long ago moved beyond being seen as just a cloud data warehouse.

Data Warehouse 130

Data Warehouse Data Science Modeling Data Governance 130

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads.

Data Warehouse 109

Data Warehouse Machine Learning Data-driven Data Lake 109

AWS Big Data

JANUARY 15, 2025

AWS Database Migration Service (AWS DMS) is used to securely transfer the relevant data to a central Amazon Redshift cluster. The data in the central data warehouse in Amazon Redshift is then processed for analytical needs and the metadata is shared to the consumers through Amazon DataZone.

IoT 109

IoT Machine Learning Metadata Data-driven 109

datapine

NOVEMBER 11, 2021

Having flexible data integration is another important feature you should look for when investing in BI software for your business. The tool you choose should provide you with different storage options for your data such as a remote connection or being stored in a data warehouse. c) Join Data Sources.

Business Intelligence 213

Business Intelligence Dashboards Interactive Visualization 213

Smart Data Collective

OCTOBER 13, 2021

Some solutions provide read and write access to any type of source and information, advanced integration, security capabilities and metadata management that help achieve virtual and high-performance Data Services in real-time, cache or batch mode. How does Data Virtualization complement Data Warehousing and SOA Architectures?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

AWS Big Data

JULY 2, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools.

Data Warehouse 116

Data Warehouse Sales Testing Big Data 116

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 132

Data Architecture Data Warehouse Statistics Visualization 132

datapine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. It allows its users to extract actionable insights from their data in real-time with the help of predictive analytics and artificial intelligence technologies. Business Intelligence Job Roles.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 144

Data mining Data-driven Statistics OLAP 144

AWS Big Data

MAY 16, 2024

As an AWS Partner, CARTO offers a software solution on the curated digital catalog AWS Marketplace that seamlessly integrates distinctive capabilities for spatial visualization, analysis, and app development directly within the AWS data warehouse environment. To learn more, visit CARTO.

Data Warehouse 117

Data Warehouse Visualization Cost-Benefit Data-driven 117

AWS Big Data

NOVEMBER 8, 2023

Because Gilead is expanding into biologics and large molecule therapies, and has an ambitious goal of launching 10 innovative therapies by 2030, there is heavy emphasis on using data with AI and machine learning (ML) to accelerate the drug discovery pipeline. Loading data is a key process for any analytical system, including Amazon Redshift.

Data Lake 103

Data Lake Data Warehouse Cost-Benefit Optimization 103

Jet Global

JULY 11, 2019

With major advances being made in artificial intelligence and machine learning, businesses are investing heavily in advanced analytics to get ahead of the competition and increase their bottom line. Demand forecasting is an area of predictive analytics best known for understanding consumer demand for goods and services.

Business Intelligence 72

Business Intelligence Forecasting Predictive Analytics Data Warehouse 72

Smart Data Collective

NOVEMBER 18, 2020

Every Data Scientist needs to know Data Mining as well, but about this moment we will talk a bit later. Where to Use Data Science? Where to Use Data Mining? Data Mining is an important research process. Practical experience.

Data mining 144

Data mining Data Science Informatics Statistics 144

DataRobot

JANUARY 20, 2022

— Snowflake and DataRobot AI Cloud Platform is built around the need to enable secure and efficient data sharing, the integration of disparate data sources, and the enablement of intuitive operational and clinical predictive analytics. Building data communities.

Data-driven 145

Data-driven Experimentation Predictive Modeling Data Warehouse 145

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. You can get faster insights without spending valuable time managing your data warehouse. Fault tolerance is built in.

Analytics 109

Analytics Data Warehouse Dashboards Testing 109

AWS Big Data

JUNE 19, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tahir Aziz is an Analytics Solution Architect at AWS.

Data Warehouse 113

Data Warehouse Testing Sales Structured Data 113

Cloudera

OCTOBER 4, 2023

Different data streams will have different characteristics, and having a platform flexible enough to adapt, with things like flexible partitioning for example, will be essential in adapting to different source volume characteristics. Kudu has this covered. The post Don’t Blink: You’ll Miss Something Amazing!

Data Warehouse 89

Data Warehouse Experimentation Cost-Benefit Dashboards 89

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. About the Authors Tahir Aziz is an Analytics Solution Architect at AWS.

Snapshot 112

Snapshot Management Data Warehouse Dashboards 112

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

CIO Business Intelligence

AUGUST 26, 2024

The strengths of AI in modern business AI’s ability to automate tasks, reduce errors, and make data-driven decisions at scale are its best lauded strengths. From predictive analytics to natural language processing (NLP), AI-powered applications enable faster and more accurate decision-making. But then what?

Data-driven 114

Data-driven Manufacturing Data Warehouse Cost-Benefit 114

CIO Business Intelligence

DECEMBER 1, 2022

Now halfway into its five-year digital transformation, PepsiCo has checked off many important boxes — including employee buy-in, Kanioura says, “because one way or another every associate in every plant, data center, data warehouse, and store are using a derivative of this transformation.”

Digital Transformation 144

Digital Transformation IoT Data-driven KPI 144

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Connect tables.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

FineReport

JUNE 24, 2021

Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. Predictive analytics and modeling.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

Sisense

MARCH 27, 2019

To provide real-time data, these platforms use smart data storage solutions such as Redshift data warehouses , visualizations, and ad hoc analytics tools. This allows dashboards to show both real-time and historic data in a holistic way. Why is Real-Time BI Crucial for Organizations?

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 117

Data Analytics Analytics Data Warehouse Data Lake 117

CIO Business Intelligence

AUGUST 3, 2023

It also used device data to develop Lenovo Device Intelligence, which uses AI-driven predictive analytics to help customers understand and proactively prevent and solve potential IT issues. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

datapine

JULY 1, 2020

Professional software has built-in predictive analytics features that are simple, yet extremely powerful. As a result, it’s possible to copy existing data into our data warehouse to speed up your workload or retain your data in-house by connecting datapine to your server remotely.

Reporting 260

Reporting Dashboards Cost-Benefit Visualization 260

AWS Big Data

AUGUST 6, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it straightforward and cost-effective to analyze your data. The ability to seamlessly integrate advanced LLMs into your Redshift environment significantly broadens the analytical capabilities of Redshift ML.

Data Warehouse 102

Data Warehouse Data-driven Modeling Internet of Things 102

AWS Big Data

JULY 25, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it straightforward and cost-effective to analyze all your data using standard SQL and your existing extract, transform, and load (ETL); business intelligence (BI); and reporting tools. Choose Store a new secret. Enter your credentials.

Management 113

Management Data Warehouse Big Data Testing 113

Cloudera

AUGUST 31, 2020

Given the prohibitive cost of scaling it, in addition to the new business focus on data science and the need to leverage public cloud services to support future growth and capability roadmap, SMG decided to migrate from the legacy data warehouse to Cloudera’s solution using Hive LLAP. The case for a new Data Warehouse?

Management 66

Management Slice and Dice Data Warehouse Analytics 66

Sisense

AUGUST 22, 2019

These are the types of questions that take a customer to the next level of business intelligence — predictive analytics. . This new type of analytics workflow means advanced analytics can happen faster, with accurate and up-to-date data. SQL, Python, and R on Periscope Data by Sisense.

Analytics 73

Analytics Business Intelligence Predictive Analytics Visualization 73

DataRobot Blog

MARCH 8, 2023

Every modern enterprise has a unique set of business data collected as part of their sales, operations, and management processes.

Enterprise 105

Enterprise Experimentation Machine Learning Data Science 105

Sisense

JUNE 30, 2020

Prescriptive analytics takes things a stage further: In addition to helping organizations understand causes, it helps them learn from what’s happened and shape tactics and strategies that can improve their current performance and their profitability. Predictive analytics is the most beneficial, but arguably the most complex type.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

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 77

Insurance Data Warehouse Data-driven Unstructured Data 77