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What is SQL Data Analysis?

Leverage SQL queries to draw data sets from your databases for in-depth analysis. By using tables and pivot tables, you can examine these data sets to uncover new patterns and trends based on your results. Effectively share your findings by creating PDF reports or exporting the data into formats such as Excel, HTML, and XML. This process allows for quick and efficient acquisition of actionable insights from your SQL data sets. You can easily sort, filter, group, and summarize your SQL data according to your needs, which provides flexibility in the arrangement of columns based on your preferences. This functionality not only aids in summarizing data but also plays a crucial role in discovering new insights and information. You have the capability to generate multiple summaries for individual columns with various functions, which can be displayed in group headers, footers, or column footers. Furthermore, you can emphasize significant values through customizable rules and formulas, enhancing your data's visual impact. Organize your data by sorting one or multiple columns either in ascending or descending order as required, and use filters to focus solely on the relevant information you want to analyze. Ultimately, this method promotes a more personalized and insightful investigation of your data, leading to enhanced decision-making and strategic planning.

What is Amundsen?

Unlock the potential of your data by fostering confidence for more impactful analysis and modeling. By breaking down barriers between information silos, you can significantly boost productivity. Instantly access insights into your data while also observing how your colleagues are utilizing it. Enjoy a seamless search experience for data within your organization using an intuitive text-based interface. The search functionality leverages an algorithm similar to PageRank, allowing for personalized recommendations based on various factors such as names, descriptions, tags, and user interactions with tables and dashboards. Build trust in your data by depending on automated, curated metadata, which offers comprehensive details about tables and columns, insights on frequent users, timestamps of the latest updates, relevant statistics, and, when allowed, previews of the data. Improve data management efficiency by establishing connections to the ETL jobs and code that create the datasets. Provide clear definitions for table and column descriptions to reduce unnecessary debates about which data to use and the meanings of individual columns. Identify which datasets are most frequently accessed, owned, or bookmarked by your peers, thereby enhancing collaboration. Furthermore, gain insights into popular queries linked to a specific table by examining dashboards created from that dataset, which enhances your analytical capabilities. Ultimately, this holistic strategy ensures that your data-driven choices are informed and anchored in trustworthy information, leading to more effective outcomes.

Media

Media

Integrations Supported

MySQL
PostgreSQL
SQL Server
Azure SQL Database
Collate
Microsoft Excel
XML

Integrations Supported

MySQL
PostgreSQL
SQL Server
AWS Glue
Amazon Web Services (AWS)
Apache Druid
Apache Hive
Apache Spark
Delta Lake
Elasticsearch
Google Cloud BigQuery
Google Cloud Platform
IBM Db2
OpenMetadata
Snowflake
Vertica

API Availability

API Availability

Pricing Information

$45 one-time payment
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

Windows

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

Yohz Software

Company Location

Malaysia

Company Website

www.yohz.com/sda_details.htm

Company Facts

Organization Name

Amundsen

Company Location

United States

Company Website

www.amundsen.io

Categories and Features

Database

Not specified

Categories and Features

Data Catalog

Not specified

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