
In 2023, IT and data leaders cited data quality, visibility, and trust in data as the top three challenges in the strategic use of data. Without reliable and transparent data pipelines, data engineers struggle to extract actionable insights from their data. These issues also make it difficult to use data to its full potential. Data intelligence platforms have become essential for overcoming these hurdles. These solutions help data leaders gain insights from large data volumes, ensuring better decision-making.
In this article, we’ll look into some top data intelligence platforms and how they can address common data challenges.
What is data intelligence?
Data intelligence is the use of tools and methods to transform raw data into actionable insights. It uses data analysis, artificial intelligence (AI), and machine learning (ML) to enable organizations to make smarter decisions through advanced data management and governance.
The key components of data intelligence platforms include:
- Data Cataloging – Organizes and indexes data for easy search and access.
- Data Mapping – Links data across various systems to ensure consistency and understanding.
- Automated Metadata Harvesting – Gathers and updates metadata automatically for more efficient data management.
- Data Analysis and Insights – Applies advanced tools to interpret data and provide meaningful insights.
- Data Lineage and Impact Analysis – Tracks data flow across systems and analyzes its impact on different processes.
What is the difference between data intelligence and business intelligence (BI)?
Business intelligence (BI) analyzes structured business data to create reports, dashboards, and trends based on past performance. It helps companies understand past events and supports decision-making through historical data insights. On the other hand, data intelligence goes beyond BI. It analyzes structured and unstructured data and uses AI and machine learning to predict trends, provide real-time insights, and comprehensively manage data.
Best data intelligence platforms
Several platforms are available to manage your data intelligence tasks. Here’s an overview of some popular ones, along with their key features, pros, and cons.
- Secoda
Secoda is an AI-powered data intelligence platform that simplifies data cataloging, discovery, and governance for modern enterprises. It integrates with your existing data stack, providing a comprehensive view of your data through automated lineage tracking and AI-powered search. This lets teams quickly locate data across columns, tables, dashboards, and metrics, helping them make faster, data-driven decisions. Secoda’s AI also helps generate documentation and queries, streamline workflows, and reduce repetitive tasks for data teams. One of Secoda’s standout features is its real-time multiplayer editing, which promotes collaboration across technical and nontechnical teams.
The platform also offers robust data governance tools, ensuring that organizations can maintain control over data access while enabling self-serve data usage. With a user-friendly interface, Secoda makes data more accessible and actionable for everyone.
- Informatica
Informatica is a comprehensive data intelligence platform that prepares data for AI and analytics. With its Intelligent Data Management Cloud (IDMC), Informatica connects, manages, and unifies data across multi-cloud and hybrid environments. The platform supports various data workloads and simplifies processes through low-code, no-code solutions. Informatica helps businesses achieve better outcomes by ensuring their data is AI-ready while offering flexible, consumption-based pricing for easier scalability.
- Collibra
Collibra is a data intelligence platform that enhances data governance, cataloging, and lineage using active metadata. Collibra helps organizations streamline decision-making and improve productivity by centralizing and automating data management. It also reduces risks across various data environments.
The platform enables collaboration between data teams and offers tools for AI governance, data quality monitoring, and privacy management. Collibra’s flexible, scalable architecture supports many integrations, making it adaptable to diverse enterprise needs.
- Alation
Alation is a data intelligence platform to help organizations maximize the value of their data and AI initiatives. By offering a robust data governance framework and tools for building trusted data products, Alation ensures data quality, transparency, and compliance. It supports collaboration across teams, enabling self-service analytics and faster decision-making. Alation also simplifies cloud migrations and integrates metadata into everyday workflows, making managing and modernizing data easier.
- Atlan
Atlan is a modern data intelligence platform that simplifies data management and boosts collaboration. It acts as a “Google for your data,” allowing users to search across their data ecosystem using natural language or SQL syntax. With features like column-level lineage and active data governance, Atlan ensures teams can easily trace and manage data. It also offers data products, a business glossary, and active metadata management to streamline data operations.
- Talend
Talend offers a comprehensive data management solution that helps organizations transform their data into valuable business insights. With its end-to-end platform, Talend Data Fabric enables data integration, quality, and governance into a single, low-code solution. It supports various data environments, allowing businesses to manage their data effectively while ensuring security and compliance. Talend’s robust tools facilitate easy data discovery, organization, and team collaboration, driving better decision-making.
- Looker
Looker is a business intelligence platform that boosts data intelligence. It helps organizations create custom data experiences and embed analytics into applications easily. Looker’s universal semantic modeling layer ensures consistent metrics across different data sources, making it easier for users to analyze and understand their data. It offers self-service analytics through enterprise dashboards and Looker Studio. Users can perform ad-hoc analysis and gain real-time insights. Looker also includes AI features to speed up analytical workflows and support data-driven decisions.
- SAP Data Intelligence
SAP Data Intelligence helps businesses manage and connect their data more effectively. It allows companies to integrate different data types, such as structured, unstructured, and streaming, into one place. With SAP Data Intelligence, organizations can create a unified view of their data. It features a data catalog that helps users quickly find and understand their data. SAP Data Intelligence brings machine learning into everyday business processes. This means companies can use advanced analytics to improve their operations and innovate faster.
- Zeenea
Zeenea is a cloud-native solution that makes it easy for organizations to access and manage their data. Its user-friendly platform democratizes data access, helping teams make informed decisions quickly. With Zeenea, businesses can accelerate their data-driven initiatives and create a culture of data collaboration.
The platform includes a data catalog and an enterprise data marketplace, providing a central data discovery and sharing hub. Zeenea helps users build a common data vocabulary while ensuring compliance and governance.
- BigID
The BigID Data Intelligence Platform helps organizations manage their data for better governance, security, and compliance. It uses advanced machine learning to discover, classify, and take action on sensitive data. This makes it easier for users to understand and control their information. BigID works with various types of data, including structured and unstructured data. It offers modular apps that focus on data privacy and protection. By unlocking the value of data, organizations can respond quickly to regulatory and industry challenges.
How to choose the right data intelligence platform for your company?
With so many available options, choosing the right tool to make the most of your company’s data becomes overwhelming.
Here are some factors to remember when making your decision:
- Assess Your Data Needs – Think about the kind of data your company handles and the insights you hope to gain. This will help you choose a platform that fits your specific goals.
- Check for Data Governance and Compliance – Ensure the platform can keep your data secure and meets industry regulations, especially if you’re handling sensitive information.
- Assess Ease of Use and User Experience – The platform should be easy to use and work well with your team’s workflow. If it’s too complicated, it could slow things down.
- Evaluate Advanced Analytics and AI Capabilities – Look for tools that offer advanced features, such as AI or machine learning, to help you extract more value from your data.
- Seek Feedback – Ask others who’ve used the platform or read reviews to learn about their experience. This can give you valuable insights into the tool’s performance in real-world situations.
- Demo Your Chosen Tool – Always try a demo or free trial. This will help you see if the platform fits your needs and is easy to work with before committing.
Source: Secoda