Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 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. Modern analytics is much wider than SQL-based data warehousing. Fault tolerance is built in. Any hardware failures are automatically replaced.

Analytics 111

Analytics Data Warehouse Dashboards Testing 111

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Jet Global

NOVEMBER 5, 2020

For more powerful, multidimensional OLAP-style reporting, however, it falls short. OLAP reporting has traditionally relied on a data warehouse. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements. Azure Data Lakes are complicated.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

Analytics 95

Analytics Data Warehouse Data Lake Metadata 95

CIO Business Intelligence

JANUARY 20, 2023

BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

AWS Big Data

SEPTEMBER 22, 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. This data must also reflect the initial creation time and last update time for auditing and tracking purposes.

Data Warehouse 124

Data Warehouse OLAP Risk Online Analytical Processing 124

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. These campaigns are optimized by using an AI-based bid process that requires running hundreds of analytical queries per campaign.

Big Data 90

Big Data Data Warehouse Advertising OLAP 90

Jet Global

APRIL 2, 2019

Many of the features frequently attributed to AI in business, such as automation, analytics, and data modeling aren’t actually features of AI at all. Which problems do disparate data points speak to? Enter data warehousing.

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. In fact, many commonly accepted best practices for designing OLTP databases could well be considered worst practices for these purely analytical systems. Analytical. Business Focus.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 114

Data Warehouse KPI Optimization Cost-Benefit 114

Jet Global

OCTOBER 7, 2020

For organizations considering a move to Microsoft Dynamics 365 Finance & Supply Chain Management (D365 F&SCM), or for those in the early stages of an implementation project, defining a clear strategy for curating data is a key to developing a comprehensive approach to reporting and analytics. Enterprise Business Intelligence.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

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

Jet Global

APRIL 10, 2019

To show you exactly what you will gain by replacing MR with Jet, we’ve compared specific features in three of our products (Jet Basics, Jet Reports and Jet Analytics) with the features you are currently using. Option 3: Jet Analytics. Jet Analytics. Multi Data Source Consolidation. Data Warehouse and OLAP Cubes.

Reporting 75

Reporting Management OLAP Data Warehouse 75

Jet Global

DECEMBER 2, 2019

Also known as “analytics,” BI looks at more expansive data relationships, perhaps even between multiple systems that collect data (such as CRM and GP), and identifies trends that can inform strategic business decisions and objectives that will improve overall performance across the entire operation.

Business Intelligence 69

Business Intelligence Reporting OLAP Data Warehouse 69

FineReport

JULY 16, 2021

When we talk about business intelligence system, it normally includes the following components: data warehouse BI software Users with appropriate analytical. Data analysis and processing can be carried out while ensuring the correctness of data. Data Warehouse. Data Analysis.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

Jet Global

JUNE 5, 2019

But data alone is not the answer—without a means to interact with the data and extract meaningful insight, it’s essentially useless. Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. Data Mining and Business Intelligence.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

Jet Global

DECEMBER 1, 2020

With Jet Analytics from insightsoftware , users in the finance and accounting department can connect easily to Microsoft Dynamics data (and to other data sources) to get immediate access to all of the information they need for robust reporting and analysis. The Easy Path to BI. Those systems contain valuable information.

Finance 78

Finance Data Warehouse OLAP Reporting 78

Jet Global

APRIL 20, 2020

First, accounting moved into the digital age and made it possible for data to be processed and summarized more efficiently. Spreadsheets enabled finance professionals to access data faster and to crunch the numbers with much greater ease. Today’s technology takes this evolution a step further.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

Jet Global

AUGUST 14, 2019

Which problems do disparate data points speak to? 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. To truly benefit from artificial intelligence, you need to set the stage with effective reporting and analytics.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

BizAcuity

AUGUST 1, 2022

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Data Security.

Reporting 52

Reporting OLAP Online Analytical Processing Dashboards 52

Sisense

FEBRUARY 16, 2021

Every aspect of analytics is powered by a data model. A data model presents a “single source of truth” that all analytics queries are based on, from internal reports and insights embedded into applications to the data underlying AI algorithms and much more. OLTP does not hold historical data, only current data.

Modeling 52

Modeling OLAP Data Warehouse Cost-Benefit 52

IBM Big Data Hub

SEPTEMBER 27, 2023

Key use cases Accelerate TDR with AI-powered unified analyst experience (UAX) QRadar Log Insights provides a simplified and unified analyst experience so your security operations team can visualize and perform analytics using all your security-related data, regardless of the location or the type of data source.

Cost-Benefit 93

Cost-Benefit OLAP Dashboards Visualization 93

Jet Global

OCTOBER 22, 2020

The world of business analytics is evolving rapidly. As ERP moves to the cloud, software vendors are developing more sophisticated, interconnected ways of gathering, organizing, and analyzing business data. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications.

Modeling 52

Modeling OLAP Reporting Sales 52

FineReport

FEBRUARY 28, 2020

And enterprise reporting is the primary data visualization technology in most enterprises. . Therefore, business intelligence is a broader category that includes data processing, perform reporting, analytics, and visualization functions. And enterprise reporting is a more specific category within BI.

Reporting 96

Reporting Enterprise Visualization Business Intelligence 96

Jet Global

APRIL 30, 2019

Built from the bones of Dynamics AX, the cloud-based Dynamics 365 Finance & Operations (D365FO) has introduced some new out-of-the-box reporting and analytical capabilities to customers. 4 Common Issues with Using Data Entities. Data entities join and link your data in D365FO to make it easier to write a report.

Finance 73

Finance OLAP Reporting Data Warehouse 73

In(tegrate) the Clouds

OCTOBER 7, 2016

As the data visualization, big data, Hadoop, Spark and self-service hype gives way to IoT, AI and Machine Learning, I dug up an old parody post on the business intelligence market circa 2007-2009 when cloud analytics was just a disruptive idea. Thanks to The OLAP Report for lots of great market materials.

Business Intelligence 40

Business Intelligence OLAP Marketing Scorecard 40

Jet Global

JANUARY 15, 2021

Power BI has definite strengths, including its tight integration with the Microsoft stack and strong data visualization capabilities, but the product is not necessarily well-suited to replace traditional reporting or analysis tools, especially so when it comes to financial reporting. Building Customer Stickiness around Reporting.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

Jet Global

JULY 29, 2020

Using OBIEE as Discoverer’s replacement is intended to help unlock the power of your information with robust reporting, ad hoc query and analysis, OLAP, dashboard, and scorecard functionality that offers the end user an experience that comes with visualization, collaboration, alert capabilities, and more. But does OBIEE stack up?

Reporting 98

Reporting Cost-Benefit Consulting Finance 98

BizAcuity

APRIL 1, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. This also applies to businesses that may not have a data warehouse and operate with the help of a backend database system.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

BizAcuity

JANUARY 31, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. This also applies to businesses that may not have a data warehouse and operate with the help of a backend database system.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

erwin

AUGUST 15, 2022

I was pricing for a data warehousing project with just 4 TBs of data, small by today’s standards. I chose “ON Demand” for up to 64 virtual CPUs and 448 GB of memory since I wanted this data warehouse to fit entirely, or at least mostly, within memory. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

Jet Global

DECEMBER 3, 2021

The term “ business intelligence ” (BI) has been in common use for several decades now, referring initially to the OLAP systems that drew largely upon pre-processed information stored in data warehouses. The use of BI and other big data technologies as value drivers continues to grow. The Future Is Now. BI has arrived.

Business Intelligence 52

Business Intelligence OLAP Sales Data Warehouse 52

Jet Global

OCTOBER 2, 2019

Which problems do disparate data points speak to? 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. To truly benefit from artificial intelligence, you need to set the stage with effective reporting and analytics.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Domino Data Lab

JULY 2, 2019

That speaks to the remarkable learning curve aspects of SQL, how oh-so-much data munging can be performed without having to sweat the details. Clearly, SQL helps reduce cognitive load for those who are learning about data management and analytics. SQL and Spark. Nope, that genie is out of the bottle.

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

Data Virtualization

MAY 5, 2020

Bring any data to any data consumer, simply and easily: that’s the goal of data virtualization. Yet contrary to what may first come to mind, data consumers are more than simply BI, analytics, or data science applications. Just about every.

Data Science 52

Data Science Analytics OLAP Data-driven 52