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4 Effective Strategies to Use Data Warehouses in Business Intelligence


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Modern tech innovations have changed the way companies operate. As businesses embrace digital technologies, they’ll generate a plethora of valuable data. Judicious use of data can help business leaders make strategic decisions to scale operations and maximize revenue.

That, in turn, has made business intelligence (BI) an indispensable part of running a business in today’s world. The right BI tools can provide you with plenty of actionable insights about business processes and systems. That, in turn, can help you optimize operations and generate a higher return on investment (ROI).

However, BI tools need accurate, organized, and structured data to function. It can become a significant challenge when you’re dealing with multiple data sources, including spreadsheets, website analytics tools, CRM platforms, etc. 

That’s where data warehouses step into the picture. They provide you with a central repository to store and organize data from different sources.

Business Intelligence and Data Warehouses: Understanding the Connection

Most BI tools lack the ability to understand raw and unstructured data. Also, they can’t collect and process data from different databases and spreadsheets. A data warehouse serves as a bridge between unstructured data and BI tools.

It combines data from multiple sources into a centralized storage platform. Also, it organizes the collected data into different rows, making it easier to find relevant information later. BI tools can use various queries to extract the required information from a data warehouse.

Furthermore, you can use data warehouses to generate department-specific data marts, i.e., curated data sets tailored to the needs of different departments and teams. That, in turn, eliminates the hassle of going through multiple rows before you can find meaningful data.

But it’s worth keeping in mind that integrating data warehouses with BI is a complex process. Here are a few techniques you should follow to maximize the benefits:

1. Outline Your Goals

The first step is to identify your reasons behind using a data warehouse and BI tools.

Do you want to use BI insights to improve customer experience? Or are you looking for ways to cut expenses and maximize revenue? Would you like a deeper insight into available human resources and optimize their performance? Or do you want to develop a better understanding of your potential customers?

Your answers to these questions will determine the types of data sources you should integrate with your data warehouse. Also, they’ll influence the type of BI tools you should use.

While you’re setting your goals, make sure you also define relevant KPIs (key performance indicators) to track and measure progress. Don’t forget to allocate a dedicated budget for your data warehouse and BI tools.

2. Identify Data Sources

Next, it’s time to identify the data sources you’ll use to generate insights and reports. Depending on your end goals, you can use various sources, such as financial statements, social media analytics, keyword research tools, etc., to collect data. The key is to identify the most relevant sources that’ll help you achieve your goals.

3. Choose Your Data Warehouse

Your choice of a data warehouse will influence the quality of insights you generate using BI tools. Typically, you can choose from the following types of data warehouses:

  • On-premise
  • Cloud-based
  • Hybrid

While on-premise data warehouses are hosted on physical servers, cloud data warehouses, such as Redshift, are hosted online on a public cloud. Hybrid data warehouses combine features of their on-premise and cloud counterparts.

Many companies are gravitating towards cloud data warehouses because of their speeds, flexibility, and scalability. If you’re planning to use one, make sure you evaluate the features of different options available online. It’s a good idea to consider a detailed ClickHouse vs. Redshift comparison before making the final decision.

Find out whether a given data warehouse separates storage and compute. Also, check whether it’s scalable and suitable for your end goals. Take the platform for a spin to analyze the learning. And make sure it integrates with any BI tools you’re already using.

4. Build Your Toolkit

While data warehouses can store and organize business data, you need other tools to feed data into them and retrieve meaningful insights. Start by looking for suitable ETL (extract, transform, load) tools that’ll help process and load data into the select data warehouse.

Also, you’ll need a host of sophisticated BI tools to query the stored data and derive relevant insights. Make sure you find easy-to-use tools that are compatible with your data warehouse. The best BI tools even help you visualize your data and convert it into meaningful reports,

In Conclusion

Combining the power of a data warehouse with modern BI tools helps you monitor business performance, make smarter decisions, and skyrocket ROI. It’s wiser to choose a feature-packed cloud data warehouse that fits your business goals. Also, use the right ETL and BI tools to harness the potential of data warehousing.

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