Top 18 Business Intelligence KPIs You Should Be Measuring in 2021

Business Intelligence KPIs List

Business Intelligence Objectives or KPIs measure the BI manager’s, analyst’s, and team’s core job efficiencies. Business Intelligence utilizes business analysis, data visualization, data mining, data tools, and data architecture to help an organization’s management make data-driven decisions.

Business Intelligence Analyst Objectives

Business Intelligence leverages software and database tools to transform data into actionable insights that inform an organization’s strategic business decisions. The purpose of the Business Intelligence objectives or KPIs is to track and measure the BI analyst’s core job efficiencies. The higher these metrics, the more successful the BI analyst.

  • Designing, developing, and maintaining business intelligence solutions – This KPI tracks and measures the BI analyst’s ability to design, develop, and maintain business intelligence solutions. The higher this metric, the more successful the analyst, and the higher the quality of actionable information available to management for strategic decision-making purposes.
  • Develop and execute ad hoc queries upon request for data – This KPI tracks and manages the BI analyst’s ability to develop and execute ad hoc queries upon request for data. The higher this metric, the greater the analyst’s ability to successfully develop and execute specific, once-off data queries.

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  • Presenting information through reports and visualization tools – A vital part of the Business Intelligence analyst’s role is to present information through reports and visualization tools in a meaningful, easy-to-understand way. This KPI tracks and measures the extent to which the BI analyst displays information using reports and data visualization tools.
  • Design, build, and deploy BI solutions like reporting tools – An essential part of the BI analyst’s role is to design, build, and deploy BI solutions like reporting and visualization tools. This KPI tracks and measures the BI analyst’s ability to create, develop, and implement required BI solutions that transform data into meaningful information.
  • Maintain and support data analytics platforms – A data analytics platform is an ecosystem of services and technologies required to analyze complex, dynamic, and voluminous data. This KPI tracks and measures the BI analyst’s ability to maintain and support the company’s data analytics platforms. The higher this metric, the greater the analyst’s ability to perform this role.
  • Create visualizations and reports for specific projects – Data visualizations and data reports are often required for individual projects. This KPI tracks and measures the BI analyst’s ability to create specific visualizations and reports for a particular project. The higher this metric, the greater the analyst’s ability to use visualizations and reports to translate data into meaningful information.
  • Set up and maintain BI tools and infrastructure – The setup and maintenance of the required BI tools and infrastructure are essential to the BI analyst’s ability to produce meaningful information from the raw data. This KPI tracks and measures the analyst’s ability to set up and maintain these Business Intelligence tools.
  • Develop and implement the BI tools’ integration with company data sources – Data is stored in warehouses, data lakes, and databases. The BI reporting and visualization tools must be integrated with the data storage sources. This KPI tracks and measures the extent to which the BI analyst is able to develop and implement the BI tools’ integration with the company data sources.
  • Implement data flow optimization methods to enhance reporting performance as required – Data flow optimization is critical to the transfer of data along the data pipelines from source to destination in the data lake or warehouse. Data must flow as quickly and efficiently as possible. This KPI tracks the BI analyst’s ability to optimize the data flow mechanisms along the data pipelines.
  • Propose new data schema to optimize data storage and data access – Structured and unstructured data flows into data storage pools like a data warehouse or a data lake. The BI analyst must continually optimize these corresponding data schema to improve reporting performance. This KPI tracks and measures the BI analyst’s ability to optimize the data scheme as required.

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Business Intelligence Manager Objectives

Business Intelligence Manager Objectives of KPIs are designed to track and measure the BI manager’s job efficiencies, or how well the BI manager fulfills their role requirements. Aspects such as knowledge gain and transfer, intra-team and company communications, and the overall evaluation and improvement of current BI systems and architectures.

  • Translate business requirements into technical specifications – This KPI tracks and measures the BI manager’s ability to translate business requirements into technical specifications. The higher this metric, the greater the analyst’s ability to create correct, easy-to-understand, and implementable technical specifications.
  • Evaluate and improve existing BI systems – The BI Manager is responsible for the overall evaluation and improvement of existing Business Intelligence systems. This KPI tracks and measures the manager’s ability to evaluate and improve existing BI systems and architectures.

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  • Collaborate with teams to integrate BI systems – Different BI systems are utilized to transform voluminous data into meaningful, easy-to-read information. For the successful integration of the other systems, the BI manager must collaborate with the different teams responsible for each system. This KPI tracks and measures the manager’s ability to work together with multiple teams.
  • Create and update technical documentation – Technical documentation describing the Business Intelligence process and the data architectures and platforms used to store, process, and transform the data into meaningful information is vital to the BI manager’s role. This KPI tracks the manager’s ability to create and update this technical documentation.
  • Improve business analysis skills – Business analysis skills are an essential part of the BI manager’s skillset. These skills must be acquired and improved upon over time and transferred to BI team members. This KPI tracks the extent to which the BI manager continually improves these business analysis skills and participates in the knowledge-sharing process.
  • Improve data analysis knowledge – Data analysis involves inspecting, cleansing, transforming, and modeling data to convert the data into meaningful information supporting strategic supporting decision-making. This KPI tracks and measures the extent to which BI manager improves data analysis knowledge and skills over time.
  • Increase current experience with BI tools – Business Intelligence tools are an integral part of the process of transforming data into meaningful information. Without an understanding of these tools, the BI manager cannot lead the process of transforming data into meaningful information. This KPI tracks and measures the manager’s continued and increasing experience with these BI Tools.
  • Collect and maintain the set of business reporting requirements – Business reporting standards are vital to ensuring that a set of business reporting standards are collected, maintained, and adhered to. The BI Manager is required to manage and implement the business reporting standards list. This KPI measures the BI manager’s ability to manage this set of business reporting requirements.
  • Implement BI reports based on the business reporting standards – Implementing the collected and managed set of business reporting standards is necessary to ensure reporting consistency and accuracy. This KPI tracks and measures the BI manager’s ability to implement these reporting standards for all BI reports. The higher this KPI, the more successful the implementation of the reporting standards.

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Business Intelligence Team Objectives

Business Intelligence Team Objectives or KPIs are designed to track and measure the BI team’s core efficiencies. Job roles include creating and maintaining data structures in data warehouses and data lakes, the development of unit testing scripts, and the development and execution of database queries that return meaningful information.

  • Create data structures, including OLAP cubes, to store data – Data structures, such as OLAP cubes, used to store data, are an integral part of the holistic management and control of the massive volumes of company data, including structured, semi-structured, and unstructured data. This KPI tracks and measures the extent to which the BI team can create these data structures.
  • Conduct unit testing and troubleshoot testing errors – Part of the Business Intelligence team’s role is to conduct unit testing by creating unit testing scripts and troubleshooting unit testing errors. This KPI tracks and measures the extent to which the analyst can implement a successful unit testing schedule.

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  • Develop and execute database queries – The development and execution of database queries is an integral part of the Business Intelligence team’s day-to-day role. This KPI tracks and measures the extent to which the analyst can develop and execute database queries that return meaningful information. The higher this metric, the higher the quality of information generated.
  • Analyze the data returned by a database query – The Business Intelligence team must analyze the data returned by a database query, including aggregation queries, to ensure that it is correct and is translatable into meaningful information. This KPI tracks and measures the team’s ability to successfully analyze this data.
  • Debug and troubleshoot issues – Data analysis system issues, including software and hardware problems, are a reality for the modern business organization. The Business Intelligence team must debug and troubleshoot these issues to resolve them. This KPI tracks and measures the analyst’s ability to debug and troubleshoot problems as they arise.
  • Collaborate with data warehouse architects, data scientists, and data collection application engineers – Meeting the company’s Business Intelligence reporting and data visualization requirements requires close collaboration with data warehouse architects, data scientists, and data collection application engineers. This KPI tracks and measures the BI team’s ability to work closely with the company’s data warehouse architects, data scientists, and data collection application engineers.

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These KPIs provide the basis to measure the Business Intelligence team’s job role efficiencies. They are vital reference points designed to monitor the BI team’s month-to-month performance, initiated by the BI manager, ensuring consistency and reliability in the company’s overall BI and data intelligence department, driving data-driven decision-making at a managerial level.

These Business Intelligence KPIs are divided into three result areas, BI analyst objectives, BI team objectives, and BI manager objectives, all designed to track and measure the three most important parts of the company’s Business Intelligence strategies, converting data into meaningful information and facilitating data-driven decision-making.

The Business Intelligence team’s successes form an indispensable part of ensuring organizational success. On the other hand, if the BI manager and team cannot meet the need for meaningful information on time and within budget, the company’s ability to meet its strategic goals will be reduced. Juxtapositionally, if the BI manager, team, and individual analyst utilize the necessary tools to transform the voluminous amounts of data the modern company gathers to transform data into meaningful information, company management can use it for strategic decision-making purposes, driving business growth and sustainability.

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