Jet Global

MAY 28, 2019

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. Table-based reporting routinely causes performance issues as well, particularly with large data sets.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

Analytics Vidhya

JUNE 7, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Data Warehousing In today’s fast-moving business environment, organizations are turning to cloud-based technologies for simple data collection, reporting, and analysis.

Business Intelligence 308

Business Intelligence Data Collection Data Science Publishing 308

Analytics Vidhya

DECEMBER 23, 2022

This article was published as a part of the Data Science Blogathon. Source: [link] Introduction In today’s digital world, data is generated at a swift pace. Data in itself is not useful unless we present it in a meaningful way and derive insights that help in making key business decisions.

Visualization 235

Visualization Business Intelligence Data Science Publishing 235

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

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 90

Data Warehouse Data Lake Analytics Data Science 90

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Cost reduction and best business practices. Overall data architecture and strategy.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

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

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 130

Data mining Data-driven Statistics OLAP 130

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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

Jen Stirrup

MAY 5, 2020

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. How can you differentiate the different opportunities to store your data in Azure?

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

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 128

Data Architecture Data Warehouse Statistics Visualization 128

CIO Business Intelligence

SEPTEMBER 14, 2023

These generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, as smaller businesses often don’t need to engineer for scale.

Analytics 132

Analytics Data Science Unstructured Data Data mining 132

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 85

Data Lake Data Warehouse Machine Learning Cost-Benefit 85

Cloudera

OCTOBER 4, 2023

Ability to handle complex analytic queries — especially when we’re using real-time analytics to augment existing business dashboards and reports with large, complex, long-running business intelligence queries typical for those use cases, and not having the real-time dimension slow these down in any way. Kudu has this covered.

Data Warehouse 86

Data Warehouse Experimentation Cost-Benefit Dashboards 86

Smarten

JANUARY 18, 2023

The Smarten system has helped the client cost-effectively shift from spreadsheet based reporting to business intelligence based centralized analysis, assessment, and reporting. Download the Case study.

Data Warehouse 52

Data Warehouse Analytics Data mining Business Intelligence 52

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 91

Data Lake Data Warehouse Machine Learning Cost-Benefit 91

CIO Business Intelligence

MAY 24, 2022

The company said that IDMC for Financial Services has built-in metadata scanners that can help extract lineage, technical, business, operational, and usage metadata from over 50,000 systems (including data warehouses and data lakes) and applications including business intelligence, data science, CRM, and ERP software.

Finance 132

Finance Management Metadata Data Quality 132

AWS Big Data

NOVEMBER 14, 2023

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it straightforward and cost-effective to analyze all your data at petabyte scale, using standard SQL and your existing business intelligence (BI) tools. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift.

Data Warehouse 60

Data Warehouse Analytics Testing Cost-Benefit 60

Data Science 101

DECEMBER 3, 2019

Building a data strategy is a great idea. It helps to avoid many of the Challenges of a Data Science Projects. General Questions Before Starting a Data Strategy. Do you have a process for solving problems involving data? What are the biggest challenges in your business? Do you have a data warehouse?

Data Strategy 84

Data Strategy Strategy Data Warehouse Dashboards 84

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 81

Data Warehouse Cost-Benefit Metadata Data-driven 81

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 80

Data Lake Data Warehouse Data-driven Optimization 80

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

Management 94

Management Data Warehouse Metrics Dashboards 94

CDW Research Hub

JULY 27, 2021

Data volumes are growing exponentially, and traditional, on-premises data warehouses are constrained, overly complex, and costly to scale. Companies feel locked into these systems as they are often tied to business-critical operations. Reduce the total cost of ownership of the data infrastructure.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

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 95

Analytics Data Warehouse Testing Dashboards 95

CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. How to prepare: No prior computer science or programming knowledge is necessary.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CIO Business Intelligence

JANUARY 20, 2023

Business intelligence definition Business intelligence (BI) is a set of strategies and technologies enterprises use to analyze business information and transform it into actionable insights that inform strategic and tactical business decisions.

Business Intelligence 141

Business Intelligence Dashboards Data mining OLAP 141

AWS Big Data

NOVEMBER 13, 2023

11:30 AM – 12:30 PM (PDT) Ceasars Forum ANT318 | Accelerate innovation with end-to-end serverless data architecture. 4:30 PM – 5:30 PM (PDT) Wynn ANT207 | Understand your data with business context. 1:00 PM – 2:00 PM (PDT) Venetian ANT201 | Accelerate innovation with real-time data. He can be reached via LinkedIn.

Analytics 112

Analytics Data Lake Data Warehouse Data-driven 112

CIO Business Intelligence

JULY 10, 2023

Rokita believes the key to making that transition is to stop thinking of data warehousing and AI/ML as separate departments with their own distinct systems. The data warehouse is about past data, and models are about future data. The first step was moving to the cloud.

Data Warehouse 89

Data Warehouse Cost-Benefit Unstructured Data Machine Learning 89

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 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

CDW Research Hub

DECEMBER 4, 2019

There are many benefits of using a cloud-based data warehouse, and the market for cloud-based data warehouses is growing as organizations realize the value of making the switch from an on-premises data warehouse.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

CIO Business Intelligence

AUGUST 9, 2022

These generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, as smaller businesses often don’t need to engineer for scale.

Analytics 123

Analytics Data Science Statistics Unstructured Data 123

Cloudera

AUGUST 8, 2022

The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Cloudera Data Engineering (Spark 3) with Airflow enabled. Cloudera Machine Learning .

Snapshot 90

Snapshot Data Warehouse Machine Learning Cost-Benefit 90

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 56

Big Data Data Warehouse Machine Learning Business Intelligence 56

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

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 112

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 112