How Do Business Intelligence Work and Do You Need to Use it?

We can see that the core definition of BI or business intelligence had remained the same over the last several decades in the industry, which is all about using data to make knowledgeable business decisions. However, with the technology evolving and expanding in many ways, the approaches to BI had changed a lot over overtime. As a result, we have seen an ever-increasing adoption of BI tools and technologies across industries over the last decade.

Examples of business intelligence in action by various businesses may largely vary. However, over the past couple of decades, BI technology had fundamentally transitioned from being a technical tool for experts to handle to more user-friendly, flexible, cloud-based software, which even the non-tech-savvy people can easily use. As a result, it has become agile and accessible than earlier, and it led to a proliferation in various BI use cases across the industries.

Even though this is the case, the most common trait in the BI tools is allowing anyone in the organization to gain instant and anywhere access to data, analyze it, and act on it without coding knowledge. There are many benefits to this widespread data culture, like bypassing the bottlenecks in workflows, reducing any grunt work, tackling the most important tasks with priority, and ultimately proving the validity of your business by taking it through the growth cycle.

However, exploring the classic examples of the BI real-time use cases is the best possible way to explore these benefits. Therefore, this article will explore the real use cases of companies implementing business intelligence to make appropriate business decisions and shape their future strategies.

The use of business intelligence

Companies now use business intelligence practices and technologies to make the raw business data usable. The objective is to make better decisions to strategize business and utilize the historical and live-streaming data in more effective ways. As BI improved a lot over the past decade, it is now much easier for the organization to benefit from it. It is mostly because business intelligence systems are now more streamlined and automated. For automation of business database systems, you can rely on services offered by professional consultants like Remote DBA.

What is a BI system?

An ideal BI system consists of data gathering, storage, knowledge management, and data analysis.

• Data gathering is the collection of information from all available sources and gathers it in one place.

• Data storage is the host of data stored in the data warehouse. An example is Amazon Redshift.

• Knowledge management is the process of disseminating all the data across the organization.

• An analysis is processing the data based on various parameters to get insights for decision-making.

Which companies use BI?

Most organizations tend to do some business intelligence types; however, it is not uncommon for many of them to do it as manual work. For example, a startup may be doing the data gathering manually by exporting the CSVs from various data sources. However, if they tend to store these data on spreadsheets or Google Drive, they act as their data warehouse. This is okay up to a particular point but not sustainable over time for most businesses.

The Business intelligence tools help manage business data in a much secure and easy to manage way and much simpler to use. In addition, the best BI tools help to automate much of these systems, as we outlined above, and allow the employees to focus more on their core tasks of analysis and taking action.

The companies also benefit more from using the BI tools as they require the employees to gain more access to data and make independent decisions. This approach is also ideal for startups, data-centric enterprises, and those who look for rapid growth. Let us further explore a couple of real-time examples of the usage of business intelligence in company operations.

Kudos

Koodos is a new startup from Rock Center of Harvard Business School, which builds the content curation technology for the Gen-Z based on user-generated data. The business model of Koodos is based on understanding the relationship between various data sets. First, they had to download the product logs as CSVs and then upload them to Google Sheets. From this, they used SQL for running queries, but as the data was not centralized, they found it tough and more time-consuming to run their experiments as intended.

Using the BI tool, Koodos was able to unify all their data to understand better the performance of their experiments and further use such insights to build more innovative products. Usage of business intelligence for uniting all the data to derive insight into your product and what you can do about it is expected to bring revolutionary changes to the business operations.

NYSHEX

New York Shipping Exchange is a shipping company that largely leverages technology to enhance its overseas shipping process. They had been functioning very well by doubling their enrollment in 2019, accounting for the business intelligence processes. NYSHEX was previously used to extract data manually from their proprietary applications and various cloud apps onto excel. Later, they decided to access data across various levels by using a BI tool named Chartio. This had been made possible by getting all data centralized into one system and making it easy for anyone, even without coding knowledge, to dive into the analysis process.

Charito offers an easy use drag-and-drop SQL builder, with which NYSHEX employees can now easily run their queries, set up custom dashboards, and fetch the reports as needed. Even those who do not know what SQL is can still extract what they need and when they need it. With this, NYSHEX had significantly advanced in its operational efficiency.

These use cases define how BI tools help organizations of various levels to outperform their competitors by fine-tuning their business operations. The future of BI is brighter and is expected to bring forth many new innovative ways in data-driven business management.