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What is a data platform?

Data platforms streamline data management and analysis to give businesses a competitive advantage.
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Data platform defined

A data platform is a comprehensive business solution that brings various data tools and capabilities together on one end-to-end system, empowering organizations to deliver value faster by simplifying data ingestion, preparation, storage, and analysis.

Key takeaways

  • Data platforms are technology solutions that provide the necessary tools for various data management workloads—including ingestion, storage, transformation, analysis, and visualization—on one system.
  • Modern data platforms use cloud-based architectures and advanced AI technologies to provide a flexible, scalable solution—and enable innovative capabilities like process automation, predictive analytics, and real-time data management.
  • Companies adopt data platforms to simplify workflows, accelerate time to insight, reduce costs, and make more informed decisions.
  • Data platforms can be built and tailored to meet specific business needs. Common types of data platforms include customer data platforms, big data platforms, and cloud data platforms.

How data platforms work

Data platforms consolidate different data storage, management, and analytics workloads to help businesses drive data efficiency and make more informed decisions. Unlike traditional data pipelines comprised of disconnected tools and systems, data management platforms provide all the necessary tools for every data workflow from within a single environment. Modern data platforms—such as Microsoft Fabric—use cloud-based infrastructures and AI capabilities to enable real-time data management and analytics capabilities in addition to greater flexibility and scalability.
Data platforms help improve each stage in the entire lifecycle of your organization’s data, including:
 
  • Ingestion. These solutions offer a unified environment to help streamline the process of collecting and integrating data from various sources, such as databases and IoT devices. Modern data platforms can also automatically gather data in real time, ensuring accuracy and reducing the need for manual data entry.

  • Storage. Unified platforms enable your business to store all data types within one centralized repository, making it easier for teams to comprehensively view and manage large volumes of data. Plus, cloud-based platforms typically use scalable data lakehouses that can adjust to meet your evolving business needs.

  • Transformation. Data platforms bring data mapping, validation, and preparation tools together on one system to help teams enhance data quality while simplifying workflows. Modern data platforms can also automate repetitive tasks like data cleaning, normalization, and enrichment to save time and accelerate time to insight.

  • Business intelligence and analytics. These solutions offer self-service analytics and visualization tools that help everyone across your business present data in easily understandable formats. Plus, modern data platforms enable real-time data processing to help teams collaborate and make timely decisions using up-to-date insights.

  • Governance and security. Data platforms consolidate business data from different sources within one place, making it easier to implement consistent governance policies and security measures across your entire data estate. Modern data platforms also use advanced encryption techniques and security protocols to better safeguard data from potential cyberthreats.

Benefits of data platforms

Replacing multiple disconnected data tools and systems with a single platform generates many benefits for your business, including:
 
  • Lower costs. Data platforms help reduce IT and administrative costs associated with maintaining multiple data tools and systems. Plus, modern data platforms offer flexible, scalable solutions with pay-as-you-go pricing models to help ensure you pay only for the services you need.

  • Better decision-making. Data platforms provide advanced data visualization tools that enable everyone, regardless of expertise, to understand insights and make informed decisions. Plus, real-time analytics capabilities help your business continuously maintain accuracy across its data pool.

  • Greater efficiency. Managing business data within one comprehensive system helps streamline operations, eliminate data silos, and reduce redundancy. Automation capabilities also reduce the number of manual tasks within various workloads, empowering teams to focus on more strategic initiatives.

  • Higher productivity. Data platforms simplify workflows with one unified environment for every tool and service, enabling everyone to easily access relevant data and quickly find valuable insights. Plus, process automation helps teams get more work done faster while minimizing errors.

  • Saved time. Centralized data management helps reduce the time spent switching between apps, searching for information, and consolidating data. Automation capabilities also save teams time by eliminating time-consuming tasks, such as data entry.

  • More valuable insights. Modern data platforms use advanced AI technologies to uncover patterns and trends that might not be visible with traditional analysis methods. For example, these solutions can predict future trends and outcomes to help your business plan strategically and mitigate potential risks.

  • Enhanced security. Data platforms offer advanced security features to more easily protect sensitive data from breaches and cyberthreats—and govern your entire data estate in compliance with regulations and standards.

  • Improved collaboration. Using a shared data management platform facilitates more effective and efficient workflows across departments, enabling teams to access the same data pool, share insights, and work together on data-driven projects.

  • Increased scalability. Cloud-based data platforms are flexible and can easily adjust to accommodate growing data volumes and evolving business needs.

  • Streamlined training. Adopting one platform to handle every data management workload simplifies employee training by significantly reducing the number of data systems teams must learn to deliver value.

Types of data platforms

While data platforms comprise a wide range of data tools and services, they can also be built and tailored to better meet specific business needs. Common types include:
Customer data platforms
Customer data platforms are designed to help businesses collect and manage customer data from across different sources to create detailed customer profiles. These solutions provide a unified environment for teams to achieve a single, comprehensive view of each customer. Companies adopt customer data platforms to better personalize marketing efforts, improve customer experiences, and drive engagement by identifying behavioral patterns and generating insights into customer preferences.

Big data platforms
Big data platforms specialize in gathering, processing, and storing huge volumes of data. These solutions enable enterprises to handle vast amounts of data spread across different servers and locations. While other data platforms may also be able to manage large volumes of data, big data platforms are designed to do so quickly—often in real time.

Cloud data management platforms
Cloud data platforms are designed to manage data across cloud environments. Like other data platforms, they provide tools for every data management and analytics workload—however, these solutions enable greater scalability, flexibility, and cost-efficiency than traditional, on-premises data platforms. These modern platforms are adjustable to meet evolving business needs and often integrate AI capabilities to reduce the complexity of various data management processes.

Data platform use cases

Data platforms help organizations gain a competitive advantage across different markets and industries, including:
 
  • Healthcare. Doctors and nurses use data platforms to help manage electronic health records and deliver improved patient experiences. Using predictive analytics, hospitals can also improve preventative care and resource allocation.

  • Finance. Financial institutions use data analytics platforms to identify patterns and anomalies—and detect fraudulent transactions in real-time. Banks use them to analyze diverse financial data and streamline risk management.

  • Manufacturing. Companies use data platforms to analyze machine data to predict equipment failures and schedule maintenance before disruptions can occur. These solutions also help monitor production processes to help ease quality control.

  • Marketing. Businesses use data platforms to analyze customer engagement and measure the effectiveness of marketing campaigns. They also enable teams to segment markets based on customer data, facilitating targeted marketing strategies.

  • Transportation and logistics. Shipping companies use data platforms to optimize delivery routes, reduce fuel consumption, and improve delivery times. These solutions can monitor vehicle performance and drive behavior to help enhance safety and efficiency.

  • Retail. Companies use data platforms to analyze customer behavior and preferences, helping teams personalize customer interactions and improve customer experiences. Plus, they can predict demand to optimize inventory levels and manage supply chains more efficiently.

Conclusion

As industries continue to become more data-driven, the ability to access, manage, and analyze your business data efficiently grows more important. Replacing multiple disconnected data tools and systems with a comprehensive data platform empowers your entire organization to uncover valuable insights faster and make more informed decisions. Consider adopting a data platform, such as Microsoft Fabric, to implement a unified approach to data management and analysis—and achieve long-term success.

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Frequently asked questions

  • No, SQL isn’t a data platform—it’s a programming language organizations use to query, update, and manage databases efficiently. Data platforms are comprehensive systems that use SQL and other data tools to provide a unified environment for every data workflow, from initial ingestion and storage to final analysis and visualization.
  • A database is a specialized system designed to help organizations store, retrieve, and manage data efficiently. However, data platforms are more comprehensive solutions that offer data storage, ingestion, transformation, analytics, and governance capabilities by bringing various data tools, including databases, together on one unified system.
  • Data platforms are comprehensive business solutions that bring various data tools and capabilities together on one end-to-end system, empowering organizations to simplify data ingestion, storage, transformation, and analysis. However, modern data platforms also use cloud-based infrastructures and AI capabilities to offer businesses additional flexibility, scalability, and real-time data management and analytics capabilities.
  • Data platforms are comprehensive systems that integrate various data management and analytics functionalities to offer a unified environment for every data workflow, including data transformation. However, data warehouses are more specialized solutions designed to simply store and analyze structured data after it has been processed and transformed.
  • To choose a data platform, you must first assess your specific needs and desired business outcomes. Consider your existing systems as well as the volume and types of data you work with to ensure the data platform you choose is compatible and effective. Finally, consider factors such as scalability, cost-efficiency, and ease of use to determine the right data platform for your business.
  • Data management evolved from flat files and hierarchical databases to relational databases in the 1970s when SQL was first introduced as the standard language for data interaction. The following decades saw the rise of centralized data management first within data warehouses, then data lakes. Today, modern data platforms like Microsoft Fabric provide scalable, cloud-based infrastructures and AI capabilities that help businesses streamline data management, processing, and analytics workflows.

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