AWS Big Data

MARCH 13, 2024

Data analytics – Business analysts gather operational insights from multiple data sources, including the location data collected from the vehicles. You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches.

Analytics 97

Analytics IoT Metadata Internet of Things 97

AWS Big Data

FEBRUARY 26, 2024

It empowers businesses to explore and gain insights from large volumes of data quickly. Amazon OpenSearch Ingestion is a fully managed, serverless data collection solution that efficiently routes data to your OpenSearch Service domains and Amazon OpenSearch Serverless collections. Install Python and jq.

Dashboards 64

Dashboards Testing Metrics Optimization 64

Alation

JANUARY 17, 2023

Data would be pulled from various sources, organized into, say, a table, and loaded into a data warehouse for mass consumption. This was not only time-consuming, but the growing popularity of cloud data warehouses compelled people to rethink this process. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

Domino Data Lab

AUGUST 20, 2019

Real-world datasets can be missing values due to the difficulty of collecting complete datasets and because of errors in the data collection process. In a curious twist of events, standardization doesn’t change the overall shape of the data—it may not look the same at first sight, but here’s another take. Section 2.2.4

Testing 68

Testing Modeling Interactive Measurement 68

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science.

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130

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