Best Data Management Software for Experian Aperture Data Studio

Find and compare the best Data Management software for Experian Aperture Data Studio in 2024

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

  • 1
    OneTrust Privacy & Data Governance Cloud Reviews
    Transparency, choice and control are key to trust. Organizations have the opportunity to leverage these moments to build trust, and provide more valuable experiences. People expect greater control over their data. We offer privacy and data governance automation to help organizations better understand and comply with regulatory requirements. We also operationalize risk mitigation to ensure transparency and choice for individuals. Your organization will be able to achieve data privacy compliance quicker and build trust. Our platform helps to break down silos between processes, workflows, teams, and people to operationalize regulatory compliance. It also allows for trusted data use. Building proactive privacy programs that are rooted in global best practice and not just reacting to individual regulations is possible. To drive mitigation and risk-based decision-making, gain visibility into unknown risks. Respect individual choice and integrate privacy and security by default in the data lifecycle.
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    erwin Data Intelligence Reviews
    erwin Data Intelligence, or erwin DI, combines data literacy and data catalog capabilities to provide greater awareness and access to data assets, guidance on how to use them, and guardrails to ensure that data policies and best practice are followed. Automatically extract, transform, and feed metadata from a variety of data sources, operational process, and data models into one central catalog. It is then made accessible and understandable through role-based, contextual views. This allows stakeholders to make strategic decisions based upon accurate insights. erwin DI supports enterprise information governance, digital transformation, and any other effort that relies upon data to achieve positive outcomes. You can schedule ongoing scans of metadata from a wide range of data sources. You can easily map data elements from source and target, including data moving, and harmonize data integration across platforms. Data consumers can easily identify and find data that is relevant to their roles.
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    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.
  • 4
    Lyftrondata Reviews
    Lyftrondata can help you build a governed lake, data warehouse or migrate from your old database to a modern cloud-based data warehouse. Lyftrondata makes it easy to create and manage all your data workloads from one platform. This includes automatically building your warehouse and pipeline. It's easy to share the data with ANSI SQL, BI/ML and analyze it instantly. You can increase the productivity of your data professionals while reducing your time to value. All data sets can be defined, categorized, and found in one place. These data sets can be shared with experts without coding and used to drive data-driven insights. This data sharing capability is ideal for companies who want to store their data once and share it with others. You can define a dataset, apply SQL transformations, or simply migrate your SQL data processing logic into any cloud data warehouse.
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