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.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

Smart Data Collective

JUNE 16, 2022

One of the most valuable tools available is OLAP. This tool can be great for handing SQL queries and other data queries. Every data scientist needs to understand the benefits that this technology offers. Using OLAP Tools Properly. Several or more cubes are used to separate OLAP databases. see more ).

Online Analytical Processing 129

Online Analytical Processing OLAP Analytics Data Warehouse 129

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. BI software solutions (by FineReport).

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

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. Choose Create workgroup.

Analytics 94

Analytics Data Warehouse Testing Dashboards 94

IBM Big Data Hub

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

OLAP 62

OLAP Slice and Dice Cost-Benefit Data Warehouse 62

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 133

Data mining Data-driven Statistics OLAP 133

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 101

Data Warehouse OLAP Risk Online Analytical Processing 101

Jet Global

DECEMBER 2, 2019

Business Intelligence Infrastructure: The overall concept of business intelligence platforms is that they take that raw, two-dimensional, live data, parse it down to only the relevant, useable pieces and then structure it, subjectize it, and finally, dimensionalize it, so the data is completely optimized for analysis.

Business Intelligence 69

Business Intelligence Reporting OLAP Data Warehouse 69

Jet Global

APRIL 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.

Enterprise 80

Enterprise OLAP Business Intelligence Internet of Things 80

FineReport

AUGUST 14, 2020

It is composed of three functional parts: the underlying data, data analysis, and data presentation. The underlying data is in charge of data management, covering data collection, ETL, building a data warehouse, etc.

Reporting 98

Reporting Informatics OLAP Data Warehouse 98

Jet Global

OCTOBER 7, 2020

Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities. The Data Entity Store is an internal data warehouse that is only available to embedded Power BI reports (not the full version of Power BI).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

OCTOBER 22, 2020

OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications. This leads to the second option, which is a data warehouse. In this scenario, data are periodically queried from the source transactional system. The first is an OLAP model.

Modeling 52

Modeling OLAP Reporting Sales 52

Jet Global

APRIL 10, 2019

Jet Analytics is a business intelligence and reporting solution with pre-built data warehouse and OLAP cubes for Dynamics GP. Multi Data Source Consolidation. Data Warehouse and OLAP Cubes. Option 3: Jet Analytics. Management Reporter. Jet Analytics. Dashboards and KPIs. Power Bi Integration.

Reporting 75

Reporting Management OLAP Data Warehouse 75

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. INTERFACE OF BI SYSTEM.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

Jet Global

DECEMBER 1, 2020

A non-developer can easily build a basic data warehouse including OLAP Cube or Tabular Model with Jet Analytics in as little as 30 minutes. This is because it lacks all the data warehouse automation and modeling features that come with Jet Analytics.

Finance 78

Finance Data Warehouse OLAP Reporting 78

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 70

Analytics Data Warehouse Data Lake Metadata 70

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

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 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

In(tegrate) the Clouds

OCTOBER 7, 2016

Thanks to The OLAP Report for lots of great market materials. Comshare, Pilot, Metaphor, watch out here comes some more: OLAP, ROLAP, HOLAP, MOLAP now my head hurts. OLAP for the masses, gents? OLAP Services, TM1, Pablo, Wired, and Crystal fun. Ad hoc query, data mining, information I’m still not finding.

Business Intelligence 40

Business Intelligence OLAP Marketing Scorecard 40

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

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.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Octopai

JANUARY 8, 2020

As a company’s data landscape grows and evolves, more computing “horsepower” is needed to perform the ETL and OLAP cube processing required to populate data warehouses and drive reports and dashboards. With automated metadata management, you can correlate data source growth with the performance of these processes.

Metadata 54

Metadata Key Performance Indicator OLAP Forecasting 54

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. As technology has evolved, BI has grown steadily more powerful, affordable, and accessible.

Business Intelligence 52

Business Intelligence Sales OLAP Data Warehouse 52

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.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

FineReport

FEBRUARY 28, 2020

The underlying data is responsible for data management, including data collection, ETL, building a data warehouse, etc. In the end, display data insights such as reports and visual charts through data presentation.

Reporting 96

Reporting Enterprise Visualization Business Intelligence 96

Jet Global

APRIL 19, 2021

This puts tremendous stress on the teams managing data warehouses, and they struggle to keep up with the demand for increasingly advanced analytic requests. To gather and clean data from all internal systems and gain the business insights needed to make smarter decisions, businesses need to invest in data warehouse automation.

Data Warehouse 98

Data Warehouse Cost-Benefit OLAP Business Intelligence 98

Smarten

JANUARY 4, 2018

Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting.

Data Warehouse 40

Data Warehouse OLAP Data Governance Optimization 40

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.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Jet Global

APRIL 30, 2019

With Jet Analytics, we provide an easy-to-setup pre-packaged set of data entities with our solution. You also get a pre-built data warehouse and cubes (tabular or OLAP) that uses these data entities to de-normalize the tables and keep all your governed data in one place.

Finance 73

Finance OLAP Reporting Data Warehouse 73

Jen Stirrup

OCTOBER 30, 2022

One particular technology which is good for summarising and aggregating data is called OLAP (On Line Analytical Processing). Historical analytics can help to support the marketing process, which can also be augmented by predictive analytics, alternatively known as data mining, which can help to identify patterns in customer behavior.

Data mining 52

Data mining Predictive Analytics Cost-Benefit OLAP 52

FineReport

JUNE 3, 2020

Data yang mendasar bertanggung jawab untuk memanajemen data, termasuk pengumpulan data, ETL, membangun gudang data, dll. Analisis data adalah tentang pengekstraksian data dari data warehouse dan menganalisisnya dengan metode analisis seperti kueri, OLAP, data mining, dan visualisasi data untuk menyimpulkan data.

OLAP 59

OLAP Business Intelligence Reporting Dashboards 59

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. OLTP vs OLAP. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing).

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Domino Data Lab

JULY 2, 2019

Of course, if you use several different data management frameworks within your data science workflows—as just about everybody does these days—much of that RDBMS magic vanishes in a puff of smoke. Some may ask: “Can’t we all just go back to the glory days of business intelligence, OLAP, and enterprise data warehouses?”

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

CIO Business Intelligence

JANUARY 20, 2023

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. Increased competitive advantage: A sound BI strategy can help businesses monitor their changing market and anticipate customer needs.

Business Intelligence 142

Business Intelligence Dashboards Data mining OLAP 142

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