CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

AWS Big Data

MAY 28, 2024

The details of each step are as follows: Populate the Amazon Redshift Serverless data warehouse with company stock information stored in Amazon Simple Storage Service (Amazon S3). Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

Unstructured Data 119

Unstructured Data Data Warehouse Structured Data Testing 119

AWS Big Data

JUNE 19, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tahir Aziz is an Analytics Solution Architect at AWS.

Data Warehouse 115

Data Warehouse Testing Sales Structured Data 115

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster.

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

CIO Business Intelligence

APRIL 14, 2022

DaaS vendors can also improve the quality of data that an organization might otherwise gather itself by correcting errors or filling in gaps and even provide big blocks of data should you need more. In this way, DaaS providers can improve your homegrown data warehouse by cross-fertilizing it with other, curated sources.

Enterprise 138

Enterprise Marketing Measurement Data-driven 138

AWS Big Data

AUGUST 15, 2024

In this post, we show how to capture the data quality metrics for data assets produced in Amazon Redshift. Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.

Data Quality 111

Data Quality Visualization Metadata Key Performance Indicator 111

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 97

Analytics Data Warehouse Data Lake Metadata 97

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. All BI software capabilities, functionalities, and features focus on data.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

Cloudera

APRIL 1, 2024

This recognition is a testament to our vision and ability as a strategic partner to deliver an open and interoperable Cloud data platform, with the flexibility to use the best fit data services and low code, no code Generative AI infused practitioner tools.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse.

Data Warehouse 98

Data Warehouse Data Lake Sales Data-driven 98

FineReport

DECEMBER 27, 2021

Enterprise BI typically functions by combining enterprise data warehouse and enterprise license to a BI platform or toolset that business users in various roles can use. Usually, enterprise BI incorporates relatively rigid, well-structured data models on data warehouses or data marts. Free Download.

Enterprise 59

Enterprise Dashboards Business Intelligence Visualization 59

Cloudera

OCTOBER 17, 2023

That includes first class support for data distribution (aka universal data distribution (link) ), edge data capture, stream filtering, independently modifiable stream processing that is accessible to analysts, and integration with data at rest for low cost accessible storage.

Data-driven 79

Data-driven Enterprise IoT Data Warehouse 79

Jet Global

OCTOBER 30, 2020

What are unstructured data? First, let’s consider what “structured” data looks like: CustomerID. Structured data are, by their very nature, orderly and predictable. Artificial intelligence is the solution to that problem, and that’s what data lakes are made to handle. CustomerName. Balance Due. XYZ Company.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. You can download the dataset and open it in a code editor such as VS Code. The sample dataset generated for you will be entirely different than what you see in the preceding example.

Data Lake 103

Data Lake Testing Snapshot Big Data 103

FineReport

APRIL 11, 2023

Free Download of FineReport What is Business Intelligence Dashboard (BI Dashboard)？ A business intelligence dashboard, also known as a BI dashboard, is a tool that presents important business metrics and data points in a visual and analytical format on a single screen.

Dashboards 40

Dashboards Business Intelligence Metrics Cost-Benefit 40

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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

Jet Global

NOVEMBER 7, 2023

The answer depends on your specific business needs and the nature of the data you are working with. Both methods have advantages and disadvantages: Replication involves periodically copying data from a source system to a data warehouse or reporting database. Empower your team to add new data sources on the fly.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

Jet Global

MARCH 13, 2024

While Microsoft Dynamics is a powerful platform for managing business processes and data, Dynamics AX users and Dynamics 365 Finance & Supply Chain Management (D365 F&SCM) users are only too aware of how difficult it can be to blend data across multiple sources in the Dynamics environment.

Reporting 52

Reporting Finance Data Quality Sales 52

Jet Global

OCTOBER 1, 2024

This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases. It directly queries structured and semi-structured data from data lakes , enabling operational dashboards and real-time analytics without the need for preprocessing.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52

Jet Global

FEBRUARY 14, 2022

Structuring data in a way that recognizes the importance of tax from the outset is far more efficient than a silo approach and common data models will be key enablers of a more holistic process.”. Download Now: Select Your Closest Time Zone -- Select One -- Business Email *.

Finance 52

Finance Recreation/Entertainment Reporting Data-driven 52

AWS Big Data

MAY 9, 2025

SageMaker Lakehouse organizes data using logical containers called catalogs , enabling teams to seamlessly query and analyze data across their entire ecosystemfrom S3 data lakes to Amazon Redshift warehousesusing familiar Apache Iceberg compatible tools. Download the PySpark script LakeHouseGlueSparkJob.py. AWS Glue 5.0

Data Lake 62

Data Lake Data Warehouse Marketing Management 62