The Right Data Sources and Tools For Your BI Project

With the vast amounts of data available, it’s more important than ever to have the right tools and data sources to make sense of it all. But with so many options to choose from, it can be overwhelming to know where to start. 

In this post, we’ll take a deep dive into the various data sources and tools that are necessary for a successful BI project. Whether you’re a seasoned pro or new to the world of BI, this guide will provide valuable insights and actionable tips to help you unlock the full potential of your data.

Data has become one of the driving forces behind every successful business, and business intelligence engineers are the experts who help organizations harness the power of their data. 

Business Intelligence Project

Business intelligence (BI) projects are structured efforts to gather, process, and analyze data for the purpose of informing business decisions. 

BI projects can involve a wide range of activities, such as extracting data from various sources, cleaning and transforming the data, creating dashboards and visualizations, and performing statistical analyses. 

The goal of a BI project is to turn raw data into actionable insights that can help organizations make better decisions and achieve their strategic objectives.

Identifying Usable Data Sources For Your BI Project

When it comes to selecting data sources, there are two main categories: internal and external

Internal vs External Sources of Information

Internal sources include information that you have collected within your own organization such as sales reports, customer demographics, performance metrics or other data related to daily operations. 

One of the main benefits of using internal data is that it is readily available and easy to access. Additionally, since you are already familiar with your own data, it can be easier to understand and analyze. However, internal data can also be biased or incomplete, and may not provide a complete picture of your industry or market.

External sources can come from market research firms, trade associations or public databases such as census reports. Depending on your goals and objectives, one source may be more suitable than another so it’s important to consider both when making a choice. 

One of the main benefits of using external data is that it can provide a broader perspective and help you understand the bigger picture. Additionally, external data can be more objective and reliable than internal data. However, external data can be harder to access, expensive, and may not be tailored specifically to your organization’s needs.

A combination of both internal and external sources can be the most effective way to get a complete and accurate picture of your data.

Collecting and Organizing Data Into Useful Sets

Once you’ve identified the best data sources for your project, it’s time to determine how they should be organized and structured into useful sets that can be analyzed in order to draw meaningful conclusions. 

Quality Control to Ensure Data Sets Meeting Requirements

Quality control helps identify any potential inaccuracies or errors in raw data before it is used so as not to skew results further down the line when crunching numbers from large volumes of information points. 

As not all datasets are created equal, look for patterns or anomalies in the data before moving forward with processing it further. 

Quality control processes involve inspecting sources of information for patterns & discrepancies such as outliers or missing values within a single dataset so that corrective actions can be taken if needed. 

Additionally all collected datasets should ideally also be created with an individualized version number and timestamp which helps ensure traceability while also supports future reanalysis when changes occur post analysis completion.

These quality assurance steps may seem tedious at first; however they play a vital role in making sure that the results generated from data pools meet specific requirements necessary for correct usage in analytical systems and report generation processes

Selecting Tools and Applications For The Business Intelligence Project

The next phase of a successful business intelligence project involves selecting appropriate tools and applications for storing, displaying and analyzing the collected data in order to answer specific questions about the company’s operations or target markets. 

Types of Tools Available for Analyzing, Storing, and Displaying Data 

There are what seems almost endless number of tools available, here are some of our favorites and the most popular used 

Data Visualisation 

Help you see patterns and trends in your data by creating charts, graphs, and other visual representations. These tools can be especially useful for large and complex data sets, as they make it easier to spot patterns and identify areas for further analysis

Our favorite data visualization tools include

• Tableau
• Power BI
• QlikView
• Looker

Example of a dashboard in Microsoft Power BI

Analysis 

These tools allow you to perform more in-depth analysis of your data. These tools can include spreadsheet software, statistical analysis software, and data mining tools. These types of tools allow you to perform calculations, create pivot tables, and perform data manipulation.

Our favorite data analysis tools, used for various tasks, are: 

• Excel
• R
• Python
• SAS

Example of data analysis with charts created in R

Data Storage

Another important tool is a data management tool, which helps you organize, store, and retrieve your data. These tools can include databases, data warehouses, and data lakes. These type of tools will allow you to store the data in a structured way, so it can be easily queried and accessed

Our most used data management tools are

• SQL Server
• MySQL
• Oracle
• MongoDB

Example of a query in SQL Server

Evaluate Each Tool to Determine Which Is Best Suited to Meet the Needs of the Project

At this stage in the process it’s important to assess each tool’s strengths and weaknesses based on its features versus price point; ultimately deciding which is best suited to meet the needs of your project, both now and down the road if changes occur later on during implementation stages.

From our experience, when selecting tools and applications for your BI project, it’s important to consider your specific needs and goals, as well as the size and complexity of your data set. 

Additionally, you should consider the learning curve of each tool and application, as well as the cost and scalability. In general, it’s a good idea to start with a small set of tools and applications, and then add more as needed

Final advice, don’t choose a tool that only one person knows and have experience from as this could impact the project if that person gets sick (which you of course never wants) or leaves the company and/or project. Then you have to get a new person up to speed both in terms of the project, but they also have to learn a new software. 

If you want to learn more about business intelligence (BI), we recommend our post Introduction to business intelligence (BI), or check out all of our posts related to business intelligence

As businesses must constantly adapt their strategies based on ever-shifting market conditions in order to remain competitively relevant over time, having an effective approach towards collecting information through intelligent selection of appropriate tools & apps paired with high quality datasets is key in paving a path towards success going forward into uncharted waters ahead!

Conclusion: Business Intelligence Project Data Sources and Tools

The success of a BI project depends on having the right data sources and tools to make sense of the vast amounts of data available. In this post, we’ve discussed the different types of data sources, internal and external, and the pros and cons of each. We’ve also discussed different types of tools for data visualization, data analysis, and data management.

It’s important to remember that the best data sources and tools for your specific project will depend on your specific needs and goals.

FAQ: Data Tools and Sources In a Business Intelligence Project