Data Lake and Data Warehouse: Why SMBs Should Have Both

Data is the most valuable asset for businesses as they rely on data insights to make decisions. Forbes research shows that companies generate around 2.5 quintillion bytes of data every day. While large enterprises have long used advanced data systems, SMBs (small and medium-sized businesses) are now realizing the importance of using their data to stay competitive.

McKinsey report mentions that data-driven companies are 23 times more likely to acquire customers and six times more likely to retain them. So, how do SMBs manage their data to drive meaningful insights for business intelligence?

Should we use a data lake? A data warehouse? Maybe both? And what is this “lakehouse” everyone is talking about? It is not about picking one or the other. It is about knowing what each does best and how they can work together to help your business succeed.

Let’s discuss data lakes and data warehouses and why SMBs should adopt both.

What Are Data Lakes & Data Warehouses?

First things first, let’s start with some definitions. 

What is a Data Lake?

A data lake is a centralized storage space that stores the data in its original form. It can store unstructured, semi-structured, and structured data. It is like a large pool where you can store everything from spreadsheets to IoT sensor logs. 

Data lakes like AWS S3 or Azure do not work like traditional databases, where data must be processed before storage. This makes them flexible and ideal for handling large amounts of diverse data. SMBs often use data lakes for machine learning and advanced analytics. However, The raw nature of data in data lakes often requires technical expertise to make it usable.

What is a Data Warehouse?

A data warehouse is a centralized repository for structured data. It organizes the data into predefined formats and schemas for better analysis and forecasts. For example, when you are running queries like “What were our top-selling products last month?”. Tools like Snowflake, Amazon Redshift, or Google BigQuery can offer fast answers by analyzing structured data. This is especially helpful for SMBs that must make timely decisions based on customer behavior or sales trends.

Data warehouses are also reliable for regulatory and compliance needs. Their structured design ensures that the data is consistent.

Why It’s Not About Choosing One or the Other

Businesses believe they have to pick one, either data lakes or data warehouses. However, this will limit the potential of what their data can do. Data lakes and data warehouses serve different purposes. Yet, combining both can unlock far greater value, especially for SMBs.

Using both a data lake and a data warehouse can help you achieve the best of both worlds. You can use both systems as part of their combined data strategy. A data lake can store all types of data, and a data warehouse can focus on processing and analyzing key information. This combination will help businesses handle their data needs without losing efficiency.

Cloud platforms offer solutions like AWS tools like Glue for ETL and Redshift Spectrum for querying data directly from S3. While these tools are powerful, they are also highly technical and require a good understanding of infrastructure and query optimization. This technical complexity can be challenging for mid-sized companies without a team of data engineers.

So, if you are worried about managing two different systems, ClicData can help!

ClicData offers an all-in-one platform that integrates the flexibility of data lakes with the analytical power of data warehouses—a data lakehouse if you will. It can help you store raw data and process it into structured formats to generate real-time insights, all in one system. This eliminates the need for extensive technical expertise while delivering the same benefits, all at a lower cost.

The Challenges Mid-Sized Companies Face

Mid-sized companies often face unique challenges when it comes to managing and using data. Here are some common hurdles:

1. Cost Concerns

Cost is a significant issue. While cloud providers like AWS, Azure, and Google Cloud Platform promote pay-as-you-go pricing, expenses can quickly add up. Your bill will continue to increase as you store more data or run more queries. For instance, querying unoptimized data in services like Redshift or BigQuery can lead to high monthly costs. Adding additional tools for ETL processes, like AWS Glue, can make the situation even more expensive.

2. Complexity of Tools

Another challenge is the complexity of using multiple tools. Cloud solutions often require combining different services, such as S3 for storage, Glue for data transformation, and Redshift for querying. Each tool has its own learning curve and management needs. Setting up user permissions, ensuring data security, and maintaining compliance can be ongoing headaches, especially for companies with small IT teams.

3. Talent Gap

There is also a talent gap to consider. Managing a complex data pipeline or hybrid architecture requires specialized skills that many mid-sized companies may not have. Hiring skilled data engineers can be expensive. Without them, you may face inefficiencies or performance issues that could lead to failure.

A Better Solution with ClicData

This is where ClicData offers a better alternative. It provides an all-in-one platform that integrates storage and analytics capabilities. ClicData also simplifies the management of separate tools and reduces complexity. It streamlines access management and enhances data security. With ClicData, you do not have to worry about the underlying infrastructure. You can simply focus on driving actionable insights from your data. 

Related topic: Why building your own data warehouse is not a good idea

How Modern Cloud Platforms Make It Easier (And Harder)

Modern cloud platforms have transformed the way businesses manage data. They offer reliable tools to help store and process data without any on-premise infrastructure. Services like Amazon S3 and Google BigQuery provide scalable solutions for businesses of all sizes.

However, choosing the right tool can make a huge difference for SMBs. You should prioritize flexibility and cost-effectiveness when designing their data strategy. For example:

• A data warehouse is the best choice if your goal is real-time reporting. But instead of setting up a complex Redshift pipeline, you can use ClicData to centralize your structured data. With ClicData, you can create dashboards quickly and save valuable time.

• A data lake is essential for businesses interested in AI or machine learning. However, managing raw data in platforms like S3 or Azure Data Lake Storage can be challenging. ClicData simplifies this by providing an integrated environment. You can store, clean, and analyze raw data without needing separate tools or extra engineering help.

ClicData provides an affordable and easy way to begin if you are just starting with data management. The platform eliminates the need to invest in multiple tools for storage, ETL, and analytics. This helps you scale your data systems gradually while keeping costs under control.

With ClicData, modern data management becomes more straightforward and efficient for mid-sized businesses at any stage of their data journey.

How to Build a Practical Strategy

SMBs should create a strategy for using both data lake and data warehouse. A clear plan will help them extract the most value from their data while controlling costs and complexity.

• Identify Your Goals: Define what you want to achieve with your data. Do you need real-time reports to track performance? Are you exploring AI or machine learning? Clear goals will help you decide which tools and systems you need.

• Evaluate Your Current Data: Review the data you currently have. Understand where it comes from and how it is currently used. This will help you identify gaps or opportunities to improve your processes.

• Choose the Right Tools: Select tools that match your business needs and budget. ClicData offers a reliable platform that combines storage and analytics in one solution. It will simplify your data management and reduce costs so you can focus on insights rather than infrastructure.

• Establish Data Governance: Create guidelines for how data will be managed. This means setting rules for data quality and security. Good data governance will ensure everyone uses the same standards for better data integrity.

• Monitor and Adjust: Review and monitor your strategy regularly to ensure it meets your goals. Check for inefficiencies, such as unused data or rising costs. Make adjustments as needed to improve performance and control expenses.

• Invest in Security and Training: Secure your systems with access controls, encryption, and regular audits. Train your team to use the tools efficiently.

Simplify Your Data Strategy with ClicData

The choice between a data lake and data warehouse is no longer about picking one over the other. Both are essential, but using traditional cloud platforms like AWS often comes with significant complexity and cost—factors that mid-sized organizations can’t afford to ignore.

ClicData provides the best of both worlds. By combining the capabilities of a data lake and data warehouse into a single, intuitive platform, it eliminates the technical barriers that typically come with managing cloud-based solutions. With lower costs, simpler security management, and built-in analytics, ClicData offers a better path forward for mid-market companies.Do not let complex tools or limited resources hold you back. Discover how ClicData can transform your data strategy and start your 15-day free trial today!