Key Takeaways

• A data platform unifies data collection, storage, processing, and delivery across the enterprise.
• It enables real-time analytics, AI, reporting, and smarter decision-making.
• Core components include data ingestion, transformation, governance, and access.
• Types: include data lakes, warehouses, lakehouses, CDPs, and ESG platforms.
• Businesses benefit from speed, agility, compliance, and an improved data-driven culture.
• Without a platform, data remains siloed, inconsistent, and hard to scale.

Introduction

Every business generates data, but not every business uses it well.

From customer transactions and marketing campaigns to supply chain updates and financial reports, valuable insights often remain buried in disconnected systems. This lack of data visibility slows down decisions and limits innovation.

A data platform changes that. It brings together all your data, structured or unstructured, from any source, into one secure, accessible foundation.

In this blog, we’ll break down what a data platform is, how it works, and why it’s essential for building a smarter, faster, and more connected business.

What is a data platform?

A data platform is a unified system that collects, stores, processes, and delivers data across an organisation. It provides a central hub where all types of data, whether from applications, devices, or databases, can be managed in one place.

Unlike basic storage solutions, a modern data platform is designed to support real-time analytics, AI models, and data-driven decisions. It ensures that data is clean, accessible, and actionable for different teams—finance, marketing, operations, or HR.

Data platforms can be deployed in the cloud, on-premise, or in hybrid environments, depending on business needs and scale.

Data platform vs data warehouse

While often used interchangeably, a data platform and a data warehouse serve different purposes.

A data warehouse is a specialised component that stores structured, historical data, mainly for reporting and business intelligence. It’s optimised for querying large volumes of data to generate insights.

A data platform, on the other hand, is much broader. It includes not just storage (like a data warehouse or lake), but also tools for data ingestion, processing, governance, access, and integration. It supports a wider range of data types (structured and unstructured) and serves multiple use cases—real-time analytics, machine learning, data visualisation, and automation.

In short, a data warehouse is part of a data platform, but a data platform is the full ecosystem that powers intelligent business operations.

Core components of a data platform architecture

A strong data platform relies on several integrated components that work together to manage the full data lifecycle—from collection to insight delivery.

Here’s a breakdown of the key elements:

Data Ingestion

This is the process of collecting data from various internal and external sources, such as ERP systems, mobile apps, IoT sensors, CRM tools, or APIs. It ensures all data flows into the platform consistently and securely.

Data Storage

Once ingested, data needs to be stored in a structured and scalable way. This includes data warehouses for structured data, data lakes for unstructured or raw data, and cloud storage for elastic capacity.

Also read: Understanding Data Warehousing: Source of Business Intelligence and Data Management Strategy For Better Business Decision-Making

Data Processing & Transformation

Data often arrives in inconsistent formats. ETL (Extract, Transform, Load) or ELT pipelines clean, convert, and prepare it for analysis, making the data reliable and usable for downstream systems.

Also read: Leverage Big Data Analytics Services for Business Decision Making

Data Governance & Security

This component ensures that data is properly managed, monitored, and protected. It includes access control, compliance (e.g., GDPR), data quality rules, audit trails, and encryption.

Data Access & Delivery

A data platform must provide users—business leaders, analysts, or systems—with access to insights via dashboards, BI tools, APIs, or machine learning models. This ensures data can be used effectively across the enterprise.

Types of data platforms

Different types of data platforms serve different business needs. Here are the most common ones:

• Enterprise Data Warehouse (EDW): Used for storing structured, historical data to support business intelligence and reporting. Optimised for running fast, complex queries.
• Data Lake: Designed to hold raw, unstructured data at scale. Ideal for storing large volumes of data that may be analysed later using big data or AI tools.
• Data Lakehouse: Combines the flexibility of data lakes with the structure and performance of a data warehouse, supporting both raw data storage and analytics in one place.
• Customer Data Platform (CDP): Consolidates customer data from different touchpoints into a unified profile—used for marketing, personalisation, and customer analytics.
• Data Analytics Platform: Focused on analysing data from various sources using built-in tools, dashboards, and machine learning models to uncover trends and insights.
• Data Integration Platform: Helps unify data from different systems (e.g., CRM, ERP, marketing tools) through APIs, connectors, and automation.
• IoT Data Platform: Specifically built to handle data from Internet of Things (IoT) devices—used in sectors like manufacturing, logistics, and smart cities.
• ESG Data Platform: Supports sustainability tracking and reporting by collecting, verifying, and visualising environmental, social, and governance (ESG) data. Explore Lestar ESG platform.
• Data Security Platform: Focused on protecting sensitive data through encryption, monitoring, threat detection, and compliance enforcement across systems.

Why does your business need a data platform?

A modern data platform isn’t just for large tech companies—it’s essential for any business that wants to grow, adapt, and make smarter decisions. Here’s why it matters:

• Unified data view: Breaks down data silos by centralising information from departments like sales, finance, HR, and operations—providing a single source of truth.
• Faster & smarter decisions: Enables real-time access to insights, allowing teams to act quickly and confidently across the business.
• AI & analytics-ready: Prepares data for advanced analytics, forecasting, and machine learning—helping businesses unlock predictive and prescriptive insights.
• Improved data governance: Ensures data is accurate, secure, and compliant, reducing risk and meeting regulatory standards.
• Cost efficiency: Eliminates the need for multiple disconnected tools and reduces manual effort, leading to long-term savings and better ROI.

Business use cases of data platforms

Data platforms power real results across industries and departments. Here are a few examples of how they’re used in practice:

• Finance: Helps monitor cash flow, detect fraud, and automate reporting using real-time, centralised financial data.
• Marketing: Creates unified customer profiles, tracks campaign performance, and optimises budgets based on cross-channel insights.
• Operations: Can use IoT and logistics data to streamline supply chains, reduce downtime, and improve demand forecasting.
• HR: Helps analyse workforce trends, optimise recruitment strategies, and support predictive hiring and retention efforts.
• ESG: Can collect and verify sustainability data across business functions to meet reporting standards and track ESG performance with clarity.

Challenges in managing data without a platform

Without a unified data platform, businesses often struggle with fragmented systems and limited visibility. Common challenges include:

• Data duplication and inconsistency: Multiple teams managing their own data leads to errors, redundancy, and conflicting reports.
• Siloed systems and poor collaboration: Disconnected platforms prevent departments from sharing insights or working from a common dataset.
• Delayed reporting and missed insights: Manual data handling slows down access to critical metrics and hampers timely decision-making.
• Compliance risks and security issues: Poor data control increases exposure to breaches and non-compliance with data protection regulations.
• Difficulty scaling AI and automation: Without clean, centralised data, deploying machine learning or automation becomes complex and unreliable.

How Mandrill supports enterprise data platforms

Mandrill helps businesses build scalable, intelligent data platforms that drive real-time decisions and digital transformation. Key areas of support include:

• End-to-end data integration and API automation: Seamlessly connect internal systems, cloud apps, and third-party platforms to create a unified, automated data flow.
• BI dashboards and data visualisation: Transform raw data into easy-to-understand dashboards that support daily decisions, strategy, and board-level reporting. Explore Business Intelligence Solutions
• Middleware to unify legacy and modern systems: Bridge gaps between older systems and modern cloud platforms—enabling smooth, real-time data exchange across your tech stack.
• AI model readiness and analytics tools: Prepare and enrich your data for advanced analytics, machine learning, and forecasting models. Read Artificial Intelligence Solutions
• ESG reporting and data compliance frameworks: Ensure your ESG data is accurate, auditable, and ready for compliance reporting. Learn about our ESG Reporting Solutions

Conclusion

A modern data platform is more than just a storage solution—it’s the backbone of smart, connected, and competitive business operations.

By centralising data, improving access, and enabling real-time insights, a data platform helps leaders make faster, more accurate decisions across every department. It supports everything from daily reporting to AI-powered forecasting, ESG compliance, and long-term strategy.

To stay ahead, businesses must move beyond siloed tools and legacy systems and invest in platforms that unlock the full value of their data.

Mandrill offers the tools, integration, and intelligence needed to build and scale enterprise data platforms with confidence. Get ready to turn your data into a strategic engine for growth.