How to Create a Winning Data Platform Strategy – Your Questions—Asked and Answered

Data is everywhere, but without the right tools, it’s just noise. Businesses today face a critical challenge: how to sift through vast amounts of data to find the insights that matter. This is where a data platform becomes invaluable. Data platforms provide a structured way to collect, organize, and analyze data from across the organization, turning fragmented information into a powerful resource for decision-making.

When it comes to data platforms, we find that organizations often have many questions: What exactly is a data platform? Do we need one? How can it benefit our business? These are important questions, especially in a world where data is increasingly central to success.

In this guide, we’ll walk through the fundamentals of a data platform strategy, covering everything from the basics of what a data platform is to practical steps for developing one that aligns with your goals. We’re here to provide answers and insights to help you make informed decisions about your organization’s data strategy.

Let’s dive into the essentials of creating a winning data platform strategy.

What is a Data Platform?

A data platform is an integrated system that allows businesses to gather, store, manage, and analyze data from various sources. It centralizes data in one place, breaking down barriers between departments and ensuring that everyone is working with the same, consistent information.

In practical terms, a data platform provides the architecture to support real-time analytics, data governance, and secure storage. It’s built to handle diverse data types and large volumes, making it possible to turn raw data into actionable insights. By using a data platform, organizations can streamline data operations, reduce redundancy, and make more informed decisions based on a complete view of their data.

With advanced features like automation, machine learning, and seamless scalability, a data platform is designed to evolve with your business. It empowers teams to quickly access and interpret data, supporting strategic initiatives and helping the organization stay agile and competitive.

Why Do I Need a Data Platform?

Data platforms will help your organization solve several common issues that limit your ability to use its business data effectively:

1. Data silos and inconsistent information: When your store data across various departments or systems, your teams often work with conflicting information. Marketing, sales, and finance may each have their own versions of key data, leading to inefficiencies and errors. A data platform solves this by unifying data from multiple sources, creating a consistent view everyone can rely on.
2. Time-consuming data management: Without a centralized platform, your organization’s employees spend hours gathering, cleaning, and organizing data before they can even start analyzing it. This type of manual effort slows down decision-making and reduces productivity. A data platform automates these processes, enabling your team to focus on analyzing insights rather than wrangling data.
3. Limited agility and scalability: As your business grows, managing increasing volumes of data becomes challenging. Traditional systems can’t quickly scale, forcing you to implement quick fixes that may not integrate well. A data platform is built for growth. It can handle expanding data needs, adapt to new data sources, and scale effortlessly as your organization evolves.
4. Security risks and compliance challenges: A Deloitte study found that only 19 percent of organizations have a strong governance structure in place, while eight percent have no data governance program. Data spread across multiple systems is more problematic to protect, leaving you vulnerable to security breaches. Managing access and maintaining compliance with regulations is often complex and fragmented. A data platform centralizes data governance, making it easier to control access, enforce security policies, and ensure compliance.
5. Missed insights and delayed decisions: Without a cohesive data strategy, valuable insights can go unnoticed, and opportunities can be missed. A data platform delivers real-time analytics and visualization tools that make insights readily available. It empowers your team to act quickly, make data-driven decisions, and stay competitive.

What Are Examples of Data Platforms?

Data platforms come in various forms, each with unique features and strengths catering to organizational needs. Here are a few prominent examples to give you a sense of what’s available:

Microsoft Fabric

Microsoft Fabric is a comprehensive, end-to-end data platform that simplifies data management and analytics. It integrates data engineering, data warehousing, and machine learning capabilities in one unified solution. With Fabric, organizations can combine structured and unstructured data from multiple sources, making it easier to derive insights. It’s particularly well-suited for businesses that rely heavily on Microsoft’s ecosystem, as it seamlessly connects with Dynamics 365, Azure, Microsoft 365, and Power BI.

Databricks

Databricks specializes in big data analytics and machine learning. Built on Apache Spark, Databricks provides a unified environment for data engineering, data science, and business analytics, allowing teams to collaborate seamlessly. Databricks also supports multiple cloud providers, including AWS, Azure, and Google Cloud, giving organizations flexibility and scalability.

Google BigQuery

Part of the Google Cloud Platform, BigQuery is a serverless data warehouse that excels at handling large datasets and running real-time analytics. It’s great for businesses that need to process and analyze vast amounts of data quickly.
The right choice for you depends on factors like your existing technology stack, data volume, and specific use cases. Velosio can help you determine the best data platform for your organization.

What Are the Building Blocks of a Modern Data Platform?

A successful data platform rests on several key components, each playing a distinct role in the data lifecycle. Here are the core building blocks to consider:

1. Data ingestion. Data ingestion involves bringing data into the platform from various sources, including databases, APIs, IoT devices, and external systems. This step ensures data flows continuously and reliably and is ready for use across the organization.
2. Data storage. Effective data storage solutions can handle diverse data types, from structured transactional data to unstructured files. Storage should be scalable and adaptable, whether you’re using data warehouses for analytics or data lakes for raw data storage.
3. Data processing. Data processing cleans, transforms, and organizes data, making it suitable for analysis. Depending on how quickly data needs to be available for insights, this stage may involve ETL (Extract, Transform, Load) processes or real-time streaming.
4. Data analytics and visualization. Analytics and visualization tools allow users to explore data, build reports, and create dashboards. This component transforms raw data into actionable insights, helping stakeholders understand and act on the information.

5. Data governance and security. Data governance ensures data quality, consistency, and compliance, while security protects data from unauthorized access and breaches. This component includes access controls, audit trails, and policies that keep data safe and compliant with regulations.

These building blocks can be part of an all-in-one data platform solution, like Microsoft Fabric, where everything is integrated into a single offering. Alternatively, you might choose a custom-built approach, using individual tools that best fit your specific needs and then connecting them into a cohesive platform. Choosing these approaches depends on your organization’s infrastructure, flexibility requirements, internal resources, and long-term strategy.

How Can I Develop a Successful Data Platform Strategy?

Building an effective data platform requires a clear strategy that aligns with your business goals and ensures you get the most value from your data. Here’s a step-by-step approach we use to help our clients develop a data platform strategy that’s both practical and adaptable:

1. Define your business objectives. Start by clarifying what you want to achieve with your data. Are you looking to improve decision-making, streamline operations, or support new products and services? By identifying specific objectives, you’ll be better equipped to tailor the platform’s features to your needs.
2. Assess your current data landscape. Take stock of your existing data sources, tools, and systems. Understanding where your data resides, how it flows, and who uses it will help you identify any gaps or redundancies. The assessment sets a baseline for designing a platform that complements your current setup while addressing areas for improvement.
3. Determine key requirements. Based on your objectives and current landscape, outline the essential features and capabilities your data platform should have. Consider factors like scalability, data integration, real-time analytics, and security. Be realistic about what’s necessary now and what can be added as your platform evolves.
4. Choose your technology approach. Decide whether it makes more sense to implement an all-in-one data platform or build a custom data stack from individual tools. An integrated platform can simplify management, but a custom-built solution may offer greater flexibility.
5. Set up data governance and security policies. Establish rules for how data will be managed, accessed, and protected. This includes defining roles and responsibilities, implementing data quality standards, and ensuring compliance with relevant regulations.
6. Develop a roadmap. Outline the steps to bring your data platform strategy to life, from pilot projects to full deployment. Include timelines, key milestones, and potential challenges. A phased approach can help you manage resources effectively and adjust as needed.
7. Invest in training and change management. Provide training and support to help users adapt to new tools and workflows. A well-planned change management strategy can minimize disruptions and promote a smoother transition. While these steps can be a helpful guide, they are certainly not the only path to success. As long as you’re making progress on your data journey, you’re doing it right. To read more about developing a data platform strategy, there’s good information in this McKinsey article, “Breaking through data-architecture gridlock to scale AI.”
   

What Are Some Best Practices for Implementing a Data Platform Strategy?

To ensure your data platform strategy is effective and sustainable, we encourage our clients to consider these best practices:

• Start with a pilot. Begin with a small-scale project to test your strategy and gather feedback. This approach allows you to refine your platform before a full rollout.
• Engage stakeholders early. Involve key stakeholders from across the organization to ensure the platform meets their needs and to build support for the initiative.
• Prioritize data quality. Clean, accurate data is essential for reliable insights. Implement data validation and cleansing processes from the start to maintain high standards.
• Automate where possible. Automate data ingestion, processing, and other routine tasks to improve efficiency and reduce the risk of human error.
• Regularly review and optimize. Continuously monitor platform performance and make adjustments as needed. A data platform should evolve with your organization’s changing requirements.
• Provide ongoing training. Keep users informed about new features and updates. Regular training ensures that your team can fully leverage the platform’s capabilities.

These practices help create a data platform that’s efficient, adaptable, and capable of delivering real value to your organization. But again, you do not have to adopt every best practice on the list to be successful.

How Velosio Can Help With Your Data Platform Strategy

While these best practices and strategies provide a solid foundation for building a data platform, there’s no one-size-fits-all approach. Every organization has unique needs, and your data platform can and should reflect what works best for you. It’s perfectly fine to take a different path or adapt these ideas to suit your business goals.

If you’re looking to explore your options or get advice tailored to your business, Velosio is here to help. Our team can guide you through the process, whether you’re just starting out or looking to enhance an existing data platform. Reach out to discuss how we can support you on your data journey.