Ever try to find that one perfect photo in the 1000s of pictures on your phone? It can feel the same trying to find valuable insights from your tons of business data. Insight (or the perfect picture) is in there, but finding it isn’t easy, especially if your data is scattered and unorganized.
When using Power BI, storing data in a data lake or data warehouse is a game-changer. Are they the same thing? Not quite. They both store data, but do it in different ways. A data lake is like everything in your camera roll, one central storage place for all your data—raw, structured, and unstructured. A data warehouse is like having your camera roll (or data) set up in well-organized albums and ready for analysis, helping you easily find those perfect insights.
In this blog post, we’ll show you the difference between a data lake and a data warehouse, how each works, and how Power BI consulting can help you figure out which approach makes the most sense for your business.
How Is a Data Lake Different From a Data Warehouse?
Let’s start at the beginning with what they are, what they’re used for, and some key differences of data lake vs. data warehouse. An experienced consultant can help you choose the best one (or a combination of both) based on your unique business needs and use cases.
Data Lakes: Your All-Access Pass to Raw Data
Data lakes ingest and store all your raw data (and we mean all of it) from structured (like database tables or Excel files), unstructured (like images or audio), and semi-structured (like webpages or XML) in one central repository. Data lakes support and scale massive amounts of data and are flexible for any data type, and can be more cost-effective than a traditional data warehouse. When properly governed, data lakes support flexibility and advanced ML/AI. Since data is not defined when it’s extracted, extract-load-transform (ELT) processes are required before analysis, which is where a skilled consultant makes a big difference.
On the downside, if not effectively managed or without proper governance in place, data lakes can become a bit messy and disorganized, slowing down query performance for business intelligence and data analytics. This can be more challenging to enforce data reliability and security.
A good consultant can help reduce these challenges. And they can set up efficient workflows like using Power BI to connect directly to data stored in Azure Data Lake Storage (ADLS) or cleaning and prepping data with Power BI dataflows before building dynamic reports and dashboards, for example.
Data lakes have a wealth of use cases across industries, from storing years of historical patient data in healthcare, to unifying customer touchpoints (like mobile and social media) for retailers, to consolidating supply chain data for manufacturers.
Data Warehouses: Where Your Insights Get Organized
As we mentioned, a key difference between a data lake and a data warehouse is that data warehouses extract data from sources and transform and clean it before loading it into the data warehouse. Data is stored in a schema that’s optimized for querying and analysis to support business intelligence and reporting. A data warehouse creates a ‘single source of truth’ for your organization. And although a bit more costly than data lakes, organizations often make the investment as warehouses speed up data prep and analysis, ensure data is consistent and accurate, and seamlessly connect to BI and analytics tools like Power BI, all working to improve decision-making.
One disadvantage is that data warehouses can struggle with semi-structured and unstructured data like streaming, log analytics, and social media data, making machine learning and AI use cases more difficult. Cost can also be a factor, as data warehouses can be expensive to implement and maintain.
Here’s the deal: it’s common for organizations to have both a data lake and a data warehouse in their analytics solution. An experienced consultant will work with you to set these up to work together, building a comprehensive, secure system for storing, processing and analyzing your data, leading to better business outcomes. They’ll also figure out when to use each and find the most cost-effective approach to maximize ROI.
What is Data Lakehouse in Power BI?
A data lakehouse is an architecture that blends the best of a data lake and a data warehouse into a modern, scalable platform. A lakehouse gives you a cost-effective solution for storing large volumes of structured, unstructured, and semi-structured data; goodbye, data silos. More importantly, it provides better data management, flexibility for various data types, and the high performance you need for BI and data analysis.
In Microsoft Fabric, a data lakehouse gives you the flexibility of a data lake and the structure of a data warehouse—pulled together to support traditional data analytics and advanced machine learning. There’s no need to juggle multiple tools since a lakehouse lets you bring the data you need (in all formats) to one place. Microsoft Fabric consulting brings the know-how to design a solution that unifies your data, with ingestion into the lakehouse using Data Factory pipelines or Dataflows Gen2 for data prep and transformation, and SQL endpoint in Fabric to query data.
Since Power BI is built into Fabric, you’ve got visualization right there too. You can connect directly to the lakehouse for reports and dashboards, including Direct Lake mode for real-time analytics. Bottom line: Microsoft Fabric lakehouses give you a modern, streamlined, and unified platform for data management and analytics. You’ll gain more strategic value from your data with real-time insights, advanced analytics, and powerful reporting for faster, data-driven decisions that keep you ahead of the competition.
Is Power BI a Data Warehouse? (And What Roles Does Fabric Play?)
No, Power BI is not a data warehouse, but it can play an important role in a modern data stack. Power BI’s heart and soul is as an analytics and visualization tool, not a storage solution; a Power BI consultant can set up Power BI as a key player. Data warehouses are for storing and managing large volumes of structured data, while Power BI comes in to connect to and analyze that data. Your data warehouse is like the backstage crew, structuring and organizing your data. Power BI is the star attraction, leveraging the data stored in the warehouse for analysis and visualization, giving a powerful performance of business intelligence for informed decisions.
What role does Microsoft Fabric play? Power BI and Fabric work together, creating a powerhouse team for data warehousing. Think of them like building and living in a well-designed home (with all the modern bells and whistles that make life a little easier). Fabric is the foundation and framework. It stores and processes your data in its central OneLake environment—in a structured data warehouse or a flexible lakehouse. Power BI is the thoughtfully designed house, connecting directly to Fabric’s data warehouse (or foundation) to analyze and visualize your data in real-time.
Like having modern amenities in your house, Fabric and Power BI relieve much of the headaches of traditional warehousing, keep everyone on the same page for better collaboration, and give you high performance at scale. Together they provide a data warehouse and lakehouse capability within OneLake that blends storage, processing, analysis, and reporting, helping to make the analytics process more streamlined for faster, better decision-making. By partnering with Microsoft Fabric consulting, they can be the ‘home designer’ that builds a solution for your unique needs.
Another subject we’d like to touch upon is data warehouse vs. data lake vs. lakehouse vs. data mesh. Yeah, that may sound a bit confusing. We’ve already discussed the differences between the first three, but what about data mesh? Data mesh is more of an organizational paradigm shift, moving away from a traditional, centralized data management approach to a more decentralized one, emphasizing domain-specific teams within an organization to own and manage their data. Clearly understanding how these all work and what’s best for your business takes the knowledge and experience of a good consultant who knows the pros and cons of each, and who has the insight to integrate your data architecture with your business goals.
Is Databricks a Data Lake or Data Warehouse? (And Where Does It Fit?)
Databricks is a data lakehouse as it combines features of data lakes and data warehouses. Data warehousing on Azure Databricks leverages Delta Lake, combining the capabilities of data warehousing with a lakehouse architecture. Databricks SQL provides tools and services that a consultant can use to build a high-performance and cost-effective data warehousing architecture that runs on your data lake. With the right guidance, Databricks can provide you with a unified platform— designed to be flexible, scalable, and cost-effective—for storing, managing, and analyzing your data.
Databricks seamless integration with Power BI and Microsoft Fabric can accelerate insights. How so? By creating a streamlined data journey from raw data to insights. Databricks Unity Catalog governs data in Delta Lake, which can be directly accessed in Fabric’s OneLake and visualized in Power BI using Direct Lake mode. This enables querying data from OneLake without importing or copying it. By eliminating the need for complex ETL pipelines and data duplication, you’ll get faster insights.
Platform Alignment is the Key: How a Consultant Can Help
Experienced consultants bring the talent to align Power BI, Microsoft Fabric, and Databricks to design a platform that’s right for your business. Here’s where we come in. We’ll assess your needs and current environment and learn from stakeholders and decision-makers what your goals are, so that we can prioritize them in our solution.
Our team are experts at making strategic architecture choices to build a strong foundation using data warehousing, data lakes, and lakehouses, combining their strengths with Fabric and Power BI for the best solution for your unique needs. We can also train your team with our expert-led, customized training to fill any knowledge gaps and help to create a solid data culture.
We know your leaders need action-ready insights that drive decisions and keep you ahead of your competitors. Let’s turn your data into insights that fuel those decisions—and your business.
Get in touch with a P3 team member