Best Data Extraction Software for Brandwatch

Find and compare the best Data Extraction software for Brandwatch in 2024

Use the comparison tool below to compare the top Data Extraction software for Brandwatch on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Dataddo Reviews

    Dataddo

    Dataddo

    $35/source/month
    Dataddo is a fully-managed, no-code data integration platform that connects cloud-based applications and dashboarding tools, data warehouses, and other data storages. Dataddo offers three main products: - Data to Dashboards, which lets users send data from online sources straight to dashboarding apps like Tableau, Power BI, and Google Data Studio for insights in record time. A free version is available for this product! - Data Anywhere, which enables users to send data from any A to any B—from apps to warehouses or dashboards (ETL, end to end), between warehouses (ETL), and from warehouses back into apps (reverse ETL). - Headless Data Integration, which allows enterprises to build their own data products on top of the unified Dataddo API and get all integrations in one. The company’s engineers manage all API changes, proactively monitor and fix pipelines, and build new connectors free of charge in around 10 business days. The platform is SOC 2 Type II certified and compliant with all major data privacy laws around the globe, including ISO 27001. From the first log-in to complete, automated pipelines, get your data flowing from sources to destinations in just a few clicks.
  • 2
    Rivery Reviews

    Rivery

    Rivery

    $0.75 Per Credit
    Rivery’s ETL platform consolidates, transforms, and manages all of a company’s internal and external data sources in the cloud. Key Features: Pre-built Data Models: Rivery comes with an extensive library of pre-built data models that enable data teams to instantly create powerful data pipelines. Fully managed: A no-code, auto-scalable, and hassle-free platform. Rivery takes care of the back end, allowing teams to spend time on mission-critical priorities rather than maintenance. Multiple Environments: Rivery enables teams to construct and clone custom environments for specific teams or projects. Reverse ETL: Allows companies to automatically send data from cloud warehouses to business applications, marketing clouds, CPD’s, and more.
  • 3
    PolyAnalyst Reviews

    PolyAnalyst

    Megaputer Intelligence

    PolyAnalyst, a data analysis tool, is used by large companies in many industries (Insurance Manufacturing, Finance, etc.). It uses a visual composer to simplify complex data analysis modeling instead of programming/coding. This is one of its most distinctive features. It can combine structured and poly-structured data for unified analysis (multiple-choice questions and open ended responses), and it can process text data from over 16+ languages. PolyAnalyst provides many features to meet comprehensive data analysis requirements, including the ability to load data, cleanse and prepare data for analysis, deploy machine learning and supervised analytics techniques, and create reports that non-analysts may use to uncover insights.
  • 4
    Data Virtuality Reviews
    Connect and centralize data. Transform your data landscape into a flexible powerhouse. Data Virtuality is a data integration platform that allows for instant data access, data centralization, and data governance. Logical Data Warehouse combines materialization and virtualization to provide the best performance. For high data quality, governance, and speed-to-market, create your single source data truth by adding a virtual layer to your existing data environment. Hosted on-premises or in the cloud. Data Virtuality offers three modules: Pipes Professional, Pipes Professional, or Logical Data Warehouse. You can cut down on development time up to 80% Access any data in seconds and automate data workflows with SQL. Rapid BI Prototyping allows for a significantly faster time to market. Data quality is essential for consistent, accurate, and complete data. Metadata repositories can be used to improve master data management.
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