Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

Metrics 52

Metrics Dashboards Sales Reporting 52

AWS Big Data

JUNE 29, 2023

Notebooks are provisioned quickly and provide a way for you to instantly view and analyze your streaming data. This pipeline could further be used to send data to Amazon OpenSearch Service or other targets for additional processing and visualization. View the stream data. Transform and enrich the data.

Data Analytics 78

Data Analytics Analytics IoT Data Lake 78

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Monjumi Sarma is a Data Lab Solutions Architect at AWS.

Data Lake 86

Data Lake Dashboards Metrics Metadata 86

AWS Big Data

MARCH 3, 2023

The solution Tricentis Analytics aims to address the challenges of high volume, near-real-time, and visually appealing reporting and analytics across the entire Tricentis product portfolio. As the files are created, another process is triggered to load the data from each customer on their schema or table on Amazon Redshift.

Software 52

Software Data Lake Testing Cost-Benefit 52

Sisense

MAY 11, 2021

Data teams dealing with larger, faster-moving cloud datasets needed more robust tools to perform deeper analyses and set the stage for next-level applications like machine learning and natural language processing. Here at Sisense, we think about this flow in five linear layers: Raw This is our data in its raw form within a data warehouse.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Birst BI

FEBRUARY 25, 2020

Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead. ADR on Snowflake will be the complete realization of Birst for Snowflake’s value.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

Jet Global

JULY 19, 2023

The General Self-Service Enhancements in the latest product release include: View/Edit Mode for a Dashboard offers further customization and engagement options for end-users. View mode must respect interactivity, responsive layout and limit operations with dashboard. Simba Partnership now offers two new options for data connectors.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

Jet Global

APRIL 24, 2024

Logi Symphony is a powerful embedded business intelligence and analytics software suite that empowers independent software vendors and application teams to embed analytical capabilities and data visualizations into your SaaS applications. These chatbots can be on any page or any content within your application.

Business Intelligence 52

Business Intelligence Dashboards Software Reporting 52

Jet Global

MAY 1, 2023

We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Plus, there is an expectation that tools be visually appealing to boot. They have mastered the art of displaying data in an intuitive way while at the same time driving effortless transactions in their products.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

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

FEBRUARY 23, 2024

Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MARCH 13, 2024

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting.

Reporting 52

Reporting Finance Data Quality Sales 52