About
PowerShell is a cross-platform task automation and configuration management framework, consisting of a command-line shell and scripting language. Unlike most shells, which accept and return text, PowerShell is built on top of the .NET Common Language Runtime (CLR), and accepts and returns .NET objects. This fundamental change brings entirely new tools and methods for automation. Unlike traditional command-line interfaces, PowerShell cmdlets are designed to deal with objects. An object is structured information that is more than just the string of characters appearing on the screen. Command output always carries extra information that you can use if you need it. If you've used text-processing tools to process data in the past, you'll find that they behave differently when used in PowerShell. In most cases, you don't need text-processing tools to extract specific information. You directly access portions of the data using standard PowerShell object syntax.
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About
PowerShellGet is a module with commands for discovering, installing, updating, and publishing PowerShell artifacts like modules, DSC resources, role capabilities, and scripts. The Find-Command cmdlet finds PowerShell commands such as cmdlets, aliases, functions, and workflows. Find-Command searches modules in registered repositories. For each command found by Find-Command, a PSGetCommandInfo object is returned. The PSGetCommandInfo object can be sent down the pipeline to the Install-Module cmdlet. Install-Module installs the module that contains the command. DSC resources can be located using the parameters Tag and RequiredVersion. Tag displays the current version of every resource that contains the specified tag in the repository. RequiredVersion needs the ModuleName parameter and the Name parameter is optional. The Name and ModuleName parameters limit the output. Use the AllVersions parameter to display a DSC resource's available versions.
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About
SQL is a domain-specific programming language used for accessing, managing, and manipulating relational databases and relational database management systems.
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About
dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow.
Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Developers interested in a cross-platform task automation and configuration management framework
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Audience
Professionals users in need of a solution with commands for discovering, installing, updating and publishing PowerShell artifacts
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Audience
Developers and database admins
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Audience
SQL users looking for a ETL solution to engineer data transformations
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Pricing
$100 per user/ month
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationMicrosoft
Founded: 1975
United States
apps.microsoft.com/store/detail/powershell/9MZ1SNWT0N5D
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Company InformationMicrosoft
United States
docs.microsoft.com/en-us/powershell/module/powershellget/
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Company InformationSQL
Founded: 1974
sourceforge.net/software/product/SQL/
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Company Informationdbt Labs
Founded: 2016
United States
www.getdbt.com
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Alternatives |
Alternatives |
Alternatives |
Alternatives |
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Categories |
Categories |
Categories |
Categoriesdbt powers the transformation layer of modern data pipelines. Once data has been ingested into a warehouse or lakehouse, dbt enables teams to clean, model, and document it so it’s ready for analytics and AI. With dbt, teams can: - Transform raw data at scale with SQL and Jinja. - Orchestrate pipelines with built-in dependency management and scheduling. - Ensure trust with automated testing and continuous integration. - Visualize lineage across models and columns for faster impact analysis. By embedding software engineering practices into pipeline development, dbt helps data teams build reliable, production-grade pipelines to accelerate time to insight, and deliver AI-ready data. dbt brings rigor and scalability to data preparation by enabling teams to clean, transform, and structure raw data directly in the warehouse. Instead of siloed spreadsheets or manual workflows, dbt uses SQL and software engineering best practices to make data preparation reliable, repeatable, and collaborative. With dbt, teams can: - Clean and standardize data with reusable, version-controlled models. - Apply business logic consistently across all datasets. - Validate outputs through automated tests before data is exposed to analysts. - Document and share context so every prepared dataset comes with lineage and definitions. By treating data preparation as code, dbt ensures that prepared datasets aren’t just quick fixes — they’re trusted, governed, and production-ready assets that scale with the business. dbt modernizes the “T” in ETL: Transformation. Instead of relying on legacy pipelines or black-box transformations, dbt empowers data teams to build, test, and document transformations directly inside the data warehouse or lakehouse. With dbt, teams can: - Transform raw data into analytics-ready models using SQL and Jinja. - Ensure reliability with built-in testing, version control, and CI/CD. - Standardize workflows across teams with reusable models and shared documentation. - Leverage modern platforms like Snowflake, Databricks, BigQuery, and Redshift for scalable transformation. By focusing on the transformation layer, dbt helps organizations shorten pipeline development cycles, reduce data debt, and deliver trusted insights faster — complementing ingestion and loading tools in a modern ELT stack. |
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Big Data Features
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Lineage Features
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
Data Preparation Features
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
ETL Features
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
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Integrations
Arroyo
Blotout
Bluefish
Claude Opus 4.1
Columns
ConvertCSV
Cyberstanc Swatbox
DQOps
Delinea Cloud Access Controller
Devin
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Integrations
Arroyo
Blotout
Bluefish
Claude Opus 4.1
Columns
ConvertCSV
Cyberstanc Swatbox
DQOps
Delinea Cloud Access Controller
Devin
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Integrations
Arroyo
Blotout
Bluefish
Claude Opus 4.1
Columns
ConvertCSV
Cyberstanc Swatbox
DQOps
Delinea Cloud Access Controller
Devin
|
Integrations
Arroyo
Blotout
Bluefish
Claude Opus 4.1
Columns
ConvertCSV
Cyberstanc Swatbox
DQOps
Delinea Cloud Access Controller
Devin
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