Data profiling tools for Snowflake

Data Profiling tools allow analyzing, monitoring, and reviewing data from existing databases in order to provide critical insights. Data profiling can help organizations improve data quality and decision-making process by identifying problems and addressing them before they arise.

Dataedo

Dataedo is a metadata management & data catalog tool with a data profiling feature. It allows you to use sample data to learn what data is stored in your data assets. You can browse min, max, average and median values, see top values, as well as value and row distribution to understand the data better before using it.

Access control: Yes
Commercial: Commercial
Desktop/Cloud: Desktop
Excel workbooks: Yes
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): Windows
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: Avg,Max,Min,Stdev
Tagging data: -
Dataedo Data Profiling
Data Profiling in Desktop

Atlan

Atlan automatically profiles your data to identify missing values, outliers & other data anomalies. Data profiles are fully configurable, and admins can schedule data profile updates, run profiles on random/stratified samples or custom filters. Atlan's data profile is an open ecosystem, allowing teams to import data quality metrics from external ecosystems like data pipeline tools for key metrics, such as timeliness, or other internal tools or frameworks.

Access control: Yes
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: Yes
Flat files: No
Free edition: No
Metadata identification: Yes
NoSQL sources: No
Runs on: (for desktop): -
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: Avg,Stdev
Tagging data: Yes

Global IDs Data Profiling Suite

Global IDs Data Profiling Suite is a data discovery and profiling tool that automates the discovery of data assets, automates data profiling, and provides an active inventory of all data assets.

Access control: No
Commercial: Commercial
Desktop/Cloud: Desktop
Excel workbooks: Yes
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): Linux
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: -
Tagging data: Yes

IBM InfoSphere Information Analyzer

IBM InfoSphere Information Analyzer provides data profiling and analysis to accurately evaluate the content and structure of your data for consistency and quality. It utilizes a reusable rules library and supports multi-level evaluations by rule record and pattern. It also facilitates the management of exceptions to established rules to help identify data inconsistencies, redundancies and anomalies, and make inferences about the best choices for structure.

Access control: Yes
Commercial: Commercial
Desktop/Cloud: Desktop
Excel workbooks: Yes
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): Linux,Windows
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: Avg,Stdev
Tagging data: Yes

DataRobot Data Prep

DataRobot Data Prep enables both novice and expert users to quickly and interactively explore, profile, clean, enrich and shape diverse data into AI assets ready for machine learning model development and deployment. It offers a visually interactive user interface that presents data in familiar tabular or spreadsheet style with no coding required. DataRobot provides profiles for every record and feature, including how many values are unique or missing and the statistical mean, standard deviation, median, minimum value, and maximum value.

Access control: Yes
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: Yes
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): -
Sensitive data discovery: No
SQL sources: Yes
Statistics of data: Avg,Max,Min,Stdev
Tagging data: Yes

Trillium Discovery

Trillium Discovery provides industry-leading data profiling at scale, designed specifically to meet the challenges presented by today’s data environments, with native connectivity to cloud and big data sources to execute data profiling tasks. It lets you visually assess the quality of your data and support data governance with comprehensive profiling, customized to your business

Access control: No
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: No
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): -
Sensitive data discovery: No
SQL sources: Yes
Statistics of data: -
Tagging data: No

Datameer

Datameer is a SaaS solution for data transformation in Snowflake. It provides a rich array of data profiling features to give your users a comprehensive view on their data, including automated visual data profiling, system-generated recommendations, and system- and user-generated data profile information, which includes documentation, properties, comments, tags, and more to provide further context and profile information on the data.

Access control: No
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: No
Flat files: No
Free edition: No
Metadata identification: Yes
NoSQL sources: No
Runs on: (for desktop): -
Sensitive data discovery: No
SQL sources: Yes
Statistics of data: -
Tagging data: Yes

MIOvantage

MIOvantage is a single solution platform that lets you profile data, run rules, deduplicate data, identify entities, generate reports, and more. From entity resolution to complex deduplication, MIOvantage builds a better, clearer picture from your data.

Access control: No
Commercial: Commercial
Desktop/Cloud: Desktop
Excel workbooks: Yes
Flat files: No
Free edition: No
Metadata identification: No
NoSQL sources: No
Runs on: (for desktop): Windows
Sensitive data discovery: No
SQL sources: Yes
Statistics of data: -
Tagging data: No

Trifacta

Trifacta is an open and interactive cloud platform for data engineers and analysts to collaboratively profile, prepare, and pipeline data for analytics and machine learning. For ease of data profiling, Trifacta automatically identifies dataset formats, schemas, specific attributes, and relationships across attributes and datasets, along with associated metadata for each dataset.

Access control: Yes
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: Yes
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): -
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: Avg,Max,Min,Stdev
Tagging data: No

DQLabs

DQLabs platform has a data profiling platform that is AI-driven and accepts data from multiple sources in different formats if necessary. The user interface is user-friendly and will allow the user to track the data profiling process and make adjustments where they feel it’s necessary. The platform algorithms will detect deep insight into the source data and increase the quality of the profiled data.

Access control: No
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: No
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): -
Sensitive data discovery: No
SQL sources: Yes
Statistics of data: -
Tagging data: Yes

Alation Data Catalog

Alation’s data profiling capabilities help reduce the time spent in the data exploration phase. With Alation’s data profile, data consumers have the metrics they need to easily discern the quality of any data object. Alation displays important characteristics, statistics, and numerical graphs about the data — enabling data scientists and data engineers to quickly take action. The data profiling now also includes new charts and customizations.

Access control: No
Commercial: Commercial
Desktop/Cloud: Cloud
Excel workbooks: No
Flat files: Yes
Free edition: No
Metadata identification: Yes
NoSQL sources: Yes
Runs on: (for desktop): -
Sensitive data discovery: Yes
SQL sources: Yes
Statistics of data: -
Tagging data: Yes

The use of data profiling tools can lead to higher-quality, more reliable data or eliminating errors that add costs to data-driven projects. Eliminating these costly errors involve processes such as:

• Collecting descriptive statistics.
• Collecting data types, length and recurring patterns.
• Tagging data with keywords, descriptions or categories.
• Performing data quality assessment.
• Discovering metadata and assessing its accuracy.

The most efficient way of handling the data profiling process is to automate it with a data management solution. We prepared a list of open-source data profiling tools that help you carry out the analysis of your data and identify the issues.