AWS Big Data

SEPTEMBER 5, 2024

If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported. In scenarios where data transformation is required, you can use Redshift stored procedures to modify data in Redshift tables. AWS Glue 4.0

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

FineReport

MARCH 31, 2024

In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. Harnessing the power of advanced APIs, automation, and AI, these tools simplify data compilation, organization, and visualization, empowering users to extract actionable insights effortlessly.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

Birst BI

FEBRUARY 25, 2020

Customers such as Crossmark , DJO Global and others use Birst with Snowflake to deliver the ultimate modern data architecture. Data never leaves Snowflake with Birst’s ability to support the reporting and self-service needs of both centralized IT and decentralized LOB teams.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

Peter James Thomas

MARCH 9, 2020

Such a model presents a series of states into which an organisation may fall with respect to its data. Data Maturity Models often adopt visual metaphors like ladders, or curves arching upwards, or – as I do myself – a flight of stairs.

Measurement 67

Measurement Data Strategy Strategy Modeling 67

AWS Big Data

APRIL 5, 2023

In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers. Showpad migrated over 70 dashboards with over 1,000 visuals. The company also used the opportunity to reimagine its data pipeline and architecture.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

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 98

Data Lake Dashboards Metrics Metadata 98

AWS Big Data

APRIL 22, 2025

OpenSearch Ingestion is capable of ingesting data from a wide variety of sources and has a rich ecosystem of built-in processors to take care of your most complex data transformation needs. In this post, we walk through how these new features work and how you can use them to accelerate your data ingestion projects.

Visualization 66

Visualization Data Transformation Management Risk 66

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. 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. Their dashboards were visually stunning.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt.

Data Transformation 54

Data Transformation Cost-Benefit Testing Data Lake 54

AWS Big Data

DECEMBER 2, 2024

AWS Glue establishes a secure connection to HubSpot using OAuth for authorization and TLS for data encryption in transit. AWS Glue also supports the ability to apply complex data transformations, enabling efficient data integration and preparation to meet your needs.

Data Lake 104

Data Lake Testing Data Integration Metadata 104

DataKitchen

JANUARY 23, 2023

Like an apartment blueprint, Data lineage provides a written document that is only marginally useful during a crisis. This is especially true in the case of the one-to-many, producer-to-consumer relationships we have on our data architecture. Are problems with data tests? Which report tab is wrong? When did it last run?

Testing 130

Testing Data Governance Data Quality Data-driven 130