Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them! Data Lakes.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

JUNE 21, 2023

In traditional databases, we would model such applications using a normalized data model (entity-relation diagram). Deriving business insights by identifying year-on-year sales growth is an example of an online analytical processing (OLAP) query. We discuss data model design for both NoSQL databases and SQL data warehouses.

Data Warehouse 82

Data Warehouse Data Lake OLAP Cost-Benefit 82

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 73

Analytics Data Warehouse Data Lake Metadata 73

Sisense

SEPTEMBER 3, 2019

OLTP vs OLAP. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). An OLAP database is best for situations where you read from the database more often than you write to it. OLAP databases excel at queries that require large table scans (e.g.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Jet Global

JUNE 5, 2019

Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. Store and manage: Next, businesses store and manage the data in a multidimensional database system, such as OLAP or tabular cubes. to analyze past events to forecast future events.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

BizAcuity

APRIL 1, 2023

KPI Analysis: the process of evaluating the performance of an organization using a set of measurable metrics infrastructure: refers to the hardware, software, and other key resources that are used to manage, maintain and analyze data within an organization. Data governance and security measures are critical components of data strategy.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

BizAcuity

JANUARY 31, 2023

KPI Analysis: the process of evaluating the performance of an organization using a set of measurable metrics infrastructure: refers to the hardware, software, and other key resources that are used to manage, maintain and analyze data within an organization. Data governance and security measures are critical components of data strategy.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

Jet Global

OCTOBER 7, 2020

They can sit inside your D365 F&SCM instance or in a separate Azure space, referred to as Bring Your Own Database (BYOD), which stores the data entities in Azure but in an SQL format that is accessible to reporting. Reference (e.g., General Ledger). Tax Codes). Master (e.g., Customers). Enterprise Business Intelligence.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

AUGUST 14, 2019

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

Enterprise 70

Enterprise OLAP Business Intelligence Cost-Benefit 70

Jet Global

MARCH 5, 2019

AI, colloquially, is used to refer to a number of computer-powered business decision drivers, including automation (not AI), data modeling (not AI), and reporting and analytics (also not AI). But are those tools powered by artificial intelligence? What are some of the core components of business intelligence?

Business Intelligence 75

Business Intelligence OLAP Visualization Reporting 75

Sisense

AUGUST 11, 2019

Typically, this involves using statistical analysis and predictive modeling to establish trends, figuring out why things are happening, and making an educated guess about how things will pan out in the future. What About “Business Intelligence”? BI is also about accessing and exploring your organization’s data.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Jet Global

APRIL 19, 2021

Data warehouse automation refers to the process of automating each part of the data warehouse lifecycle by minimizing manual code writing and automating the repetitive, labor-intensive, time-consuming tasks normally associated with a data warehouse. These tasks include up-front analysis, design, and modeling. Reclaim Developer Hours.

Data Warehouse 98

Data Warehouse Cost-Benefit OLAP Business Intelligence 98

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift ML makes it straightforward for data scientists to create, train, and deploy ML models using familiar SQL. To create it, refer to Tutorial: Get started with Amazon EC2 Windows instances. To download and install AWS SCT on the EC2 instance that you created, refer to Installing, verifying, and updating AWS SCT.

Analytics 98

Analytics Data Warehouse Testing Dashboards 98

Jet Global

OCTOBER 2, 2019

The optimized data warehouse isn’t simply a number of relational databases cobbled together, however—it’s built on modern data storage structures such as the Online Analytical Processing (or OLAP) cubes. Cubes are multi-dimensional datasets that are optimized for analytical processing applications such as AI or BI solutions.

Enterprise 40

Enterprise OLAP Business Intelligence Cost-Benefit 40

Jet Global

JANUARY 15, 2021

In this respect, we often hear references to “switching costs” and “stickiness.” In many respects, it is more akin to some of the very complex data warehousing and OLAP tools of the past–perhaps with an even steeper learning curve. When the cost of switching to a new product is high, customers tend to remain where they are.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. Using ML models to search more effectively brought the search space down to 102—which can run on modest hardware. Model-Driven Data Queries. Introduction. BTW, videos for Rev2 are up: [link]. That’s impressive.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Jet Global

MAY 28, 2019

A data warehouse stores transactional level details and serves the broader reporting and analytical needs of an organization – creating one source of truth for building semantic models or serving structured, simplified and harmonized data to tools like Power BI, Excel or even SSRS. Enhancing a Data Warehouse with Cubes.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

AWS Big Data

MARCH 20, 2023

Top line revenue refers to the total value of sales of an organization’s services or products. Personalized recommendations – User behavior based on clickstream events can be captured up to the last second before enriching it for personalization and sending it to the model to predict the recommendations.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

Jet Global

MAY 1, 2023

These licensing terms are critical: Perpetual license vs subscription: Subscription is a pay-as-you-go model that provides flexibility as you evaluate a vendor. Pricing model: The pricing scale is dependent on several factors. It is organized to create a top-down model that is used for analysis and reporting.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52