Business intelligence (BI) and analytics is a rapidly evolving — and growing — field. At its core, BI is about helping businesses analyze their data and make better, data-driven decisions. The goal is to discover actionable insights that executives and other business leaders can use to guide the direction of their companies.
BI and analytic platforms constantly come out with new trends and features that serve this goal. Currently, some of the top trends in the industry include increased emphasis on artificial intelligence (AI) and natural language processing (NLP), as well as more data visualizations and data automation.
If your enterprise plans to use BI and analytics platforms, properly integrating those platforms with your existing systems is key. Learn how below.
Why are More Enterprises Turning to Business Intelligence Platforms?
The business landscape today is incredibly competitive. As a result, companies need to move quickly and make the best possible decisions at every turn to stay ahead. But how can they do that? For many companies, the answer is by leveraging BI and analytic platforms.
Enterprises increasingly turn to business intelligence platforms because they offer the data-based insights to fuel strong decision-making. Between 2023 and 2030, the BI market size is expected to grow from $29 billion to nearly $55 billion. That’s incredibly strong growth that reflects the booming interest in BI platforms.
Accessing actionable insights is likely the primary motivator for business leaders choosing BI platforms, but it’s not the only one. Business intelligence can also offer businesses other benefits, including:
- Greater visibility into business operations
- Access to real-time data and analysis
- A deeper understanding of customers
- Improved reporting capabilities
- Greater efficiency
- Revenue growth
How to Integrate BI and Analytic Platforms with other Enterprise Systems
Let’s say that you’re interested in taking advantage of the benefits of BI and analytic platforms. What do you need to do to get those systems up and running in your business?
After getting your team on board and selecting the right BI platform for your needs, you need an implementation plan. This plan will lay out the whole process of implementing the new software at your company, from the very first step to getting over the finish line. In addition, that implementation plan must include details about integrating your new BI and analytics platform with other enterprise systems.
Though it may sound easy enough, integrating your data analysis platforms with your existing systems can be tricky. So apply these best practices to make the process as smooth as possible:
Identify all Your Data Sources
To integrate your data sources with your new BI analytic platform system, you need to identify and locate all those data sources. Integration will be impossible if you don’t know exactly what data you’re collecting and which pipelines that data’s moving through.
Consult with your IT team to identify all your enterprise systems and the data they collect. Your IT team should have a complete inventory of all the applications, tools, and databases your company collects.
Understand how your data moves from one system to another. You may already have data integration solutions in place which will impact your implementation plan. Take your time to make sure you don’t miss anything during this step. You don’t want to create a plan for integrating your BI software with all your systems only to realize you missed one and need to backtrack.
Develop a BI Strategy
Randomly connecting each of your systems to the BI platform one at a time isn’t the best way forward. Instead, develop a BI strategy — including your plans for integrating each existing system with the BI platform.
Your BI strategy should detail your vision of successfully using the platform. What are you hoping to get out of implementing this tool? Develop a strategy around that clear goal. Consider other factors like data governance, your technology needs, and the KPIs you want to track as well.
As you’re putting together this strategy, designate a BI team. Each member of the BI team should have their own roles and responsibilities related to integrating the BI analytic platforms with your existing systems.
Plan the BI architecture
Before you start connecting any systems, map out all the components of your BI architecture. Ask yourself, how will data get from each enterprise system to your BI platform? What tools will you use to help with data integration, if any?
By the end of this planning stage, you should know exactly how data moves from each system and reaches your BI platform. Finding the best arrangement for your BI architecture may take some trial and error.
Don’t worry if you end up needing to adjust this slightly once everything is active. This map is just an important jumping-off point to get everyone on the same page and working toward successful integration.
Consider Data Security
Whenever you introduce a new system into your data environment, there’s an increased risk of data breaches. Before you implement your new BI software, consider stepping up your data security measures.
Be sure to adjust the platform’s permissions to control who is able to access what within the system. Once integrated, BI platforms bring all your data together, which can create new security concerns. Manage access to your data sets with authorizations, proper security measures, and new security protocols.
Final points
Implementing BI and analytic platforms takes some time and effort upfront, but it will pay dividends for years to come. Once your BI platform is up and running, your business will have access to new insights and real-time analysis capabilities. It’s a powerful tool that gives your business a crucial edge over competitors.
As you connect your new BI platform to your existing systems, focus on mapping everything out, creating a strategy, and emphasizing data security. You can even use data integration tools instead of a manual approach to make the process go faster. Contact Live Earth to learn more about getting started with BI and analytic platforms.