AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 106

Data Warehouse Testing Data Quality Reporting 106

FineReport

MARCH 7, 2024

Data Analysis Report (by FineReport ) Note: All the data analysis reports in this article are created using the FineReport reporting tool. Leveraging the advanced enterprise-level web reporting tool capabilities of FineReport , we empower businesses to achieve genuine data transformation. Try FineReport Now 1.

Dashboards 52

Dashboards Reporting Advertising Statistics 52

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. This means establishing and enforcing policies and processes, standards, roles, and metrics. Why Is Data Governance in Healthcare Important? Data governance is the solution to these challenges.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

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

AWS Big Data

DECEMBER 21, 2023

For the downstream consumption by all departments across the organization, smava’s Data Platform team prepares curated data products following the extract, load, and transform (ELT) pattern. The data products from the Business Vault and Data Mart stages are now available for consumers.

Data Lake 90

Data Lake Data Warehouse Data-driven B2B 90

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. 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