Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. And continuous transformation is still time-consuming.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. Melody Yang is a Senior Big Data Solutions Architect for Amazon EMR at AWS.

Big Data 105

Big Data Data Processing Interactive Testing 105

CDW Research Hub

JULY 23, 2021

Snowflake is the data cloud that boasts instant elasticity, secure data sharing and per-second pricing across multiple clouds. Its ability to natively load and use SQL to query semi-structured and structured data within a single system simplifies your data engineering. Learn about current trends.

Structured Data 52

Structured Data Consulting Strategy Data Strategy 52

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

AWS Big Data

JULY 31, 2023

This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. We use Amazon Redshift as the data warehouse to implement the data mart solution. Under Transforms , choose SQL Query.

Sales 52

Sales Data Warehouse Visualization Testing 52

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

CDW Research Hub

OCTOBER 20, 2020

Snowflake is a modern cloud data platform that boasts instant elasticity, secure data sharing and per-second pricing across multiple clouds. Its ability to natively load and use SQL to query semi-structured and structured data within a single system simplifies your data engineering. Have questions?

Dashboards 72

Dashboards Reporting Data Warehouse Structured Data 72

AWS Big Data

DECEMBER 17, 2024

dbt provides a SQL-first templating engine for repeatable and extensible data transformations, including a data tests feature, which allows verifying data models and tables against expected rules and conditions using SQL. AWS offers several services that are compatible with dbt, including Amazon Redshift and AWS Glue.

Data Quality 91

Data Quality Testing Metrics Optimization 91

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

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 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