Jet Global

NOVEMBER 5, 2020

Ostensibly, the new product represents Microsoft’s transition to a newer, more cloud-friendly ERP for midsized enterprises. For more powerful, multidimensional OLAP-style reporting, however, it falls short. OLAP reporting has traditionally relied on a data warehouse.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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

AUGUST 14, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

FineReport

AUGUST 14, 2020

With the development of enterprise informatization, there are more and more kinds of data produced, and the demand for reports surges day by day. Many enterprises are eager to build a reporting system to solve the problems of report generation and management. There are two ways for enterprises to build reporting systems.

Reporting 98

Reporting Informatics OLAP Data Warehouse 98

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 144

Business Intelligence Dashboards Data mining OLAP 144

FineReport

JUNE 24, 2021

Business intelligence solutions are a whole combination of technology and strategy, used to handle the existing data of the enterprises effectively. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. BI software solutions (by FineReport).

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

FineReport

JULY 16, 2021

Among these problems, one is that the third party on market data analysis platform or enterprises’ own platforms have been unable to meet the needs of business development. With the advancement of information construction, enterprises have accumulated massive data base. Data Warehouse. Data Analysis.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

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 113

Data Warehouse KPI Optimization Cost-Benefit 113

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

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

DECEMBER 2, 2019

Both are paramount to business operations and both are required for an enterprise to function, thrive and compete. The start of this process is typically accomplished through the use of a data warehouse, which is a separate environment entirely from your production database. It’s important to clarify upfront that the “vs.”

Business Intelligence 69

Business Intelligence Reporting OLAP Data Warehouse 69

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

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 111

Analytics Data Warehouse Dashboards Testing 111

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 94

Analytics Data Warehouse Data Lake Metadata 94

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. Making Sense of Disparate Systems.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

Octopai

JANUARY 8, 2020

Senate that could be the nation’s first federal-level data privacy law. Smart enterprises will keep an eye on this one and invest in the automated tools needed for compliance. For example: – Business forecasting – Accurate, reliable business forecasts are essential for enterprises to determine annual resource allocations.

Metadata 72

Metadata Key Performance Indicator OLAP Forecasting 72

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. Online Analytical Processing (OLAP).

Reporting 52

Reporting OLAP Online Analytical Processing Dashboards 52

Jet Global

OCTOBER 2, 2019

While the technology behind enabling computers to simulate human thought has been developing, at times slowly, over the past half-century, the cost of implementation, readily available access to cloud computing, and practical business use cases are primed to help AI make a dramatic impact in the enterprise over the next few years.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Jet Global

JULY 29, 2020

For users of Oracle E-Business Suite (EBS), data access is about to get a bit more difficult now that the company has phased out the Oracle Discoverer product. As a heavyweight in the world on enterprise software, Oracle makes a lot of companies scramble any time it decides to stop supporting one of its core products. What Comes Next?

Reporting 98

Reporting Cost-Benefit Consulting Finance 98

Sisense

FEBRUARY 16, 2021

Data warehouses have become intensely important in the modern business world. For many organizations, it’s not uncommon for all their data to be extracted, loaded unchanged into data warehouses, and then transformed via cleaning, merging, aggregation, etc. OLTP does not hold historical data, only current data.

Modeling 52

Modeling OLAP Data Warehouse Cost-Benefit 52

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

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

Business Intelligence 52

Business Intelligence OLAP Sales Data Warehouse 52

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 Data Science Machine Learning Data-driven 105

Jen Stirrup

OCTOBER 30, 2022

There are lots of definitions out there, but I like the Gartner one best: “ A broad category of applications and technologies for gathering, storing, analysing, sharing and providing access to data to help enterprise users make better business decisions.”

Data mining 52

Data mining Predictive Analytics Cost-Benefit OLAP 52

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. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

IBM Big Data Hub

SEPTEMBER 25, 2023

They set up a couple of clusters and began processing queries at a much faster speed than anything they had experienced with Apache Hive, a distributed data warehouse system, on their data lake. Uber chose Presto for the flexibility it provides with compute separated from data storage.

OLAP 86

OLAP Data Lake Data-driven Online Analytical Processing 86

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

MAY 1, 2023

Traditional BI Platforms Traditional BI platforms are centrally managed, enterprise-class platforms. These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Requirement ODBC/JDBC Used for connectivity.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

SEPTEMBER 22, 2023

However, the complexity of Microsoft Dynamics data structures serves as a roadblock, making it difficult to use Power BI without a proper connection to your data. Dynamics ERP systems demand the creation of a data warehouse to ensure fast query response times and that data is in a suitable format for Power BI.

Visualization 52

Visualization Reporting Data Warehouse OLAP 52

Jet Global

MAY 6, 2022

Their combined utility makes it easy to create and maintain a complete data warehouse solution with very little effort. Jet acts as the perfect conduit between your ERP data and Power BI. Jet Analytics provides data warehouse automation for fast, consistent business analytics and master data management.

Data Warehouse 52

Data Warehouse Visualization Finance Reporting 52