In a mission to equip professionals with the skills and knowledge for navigating today’s business landscape, The KPI Institute joins forces with maentae, a progressive learning solution provider, to develop a course on harnessing the power of artificial intelligence (AI).

AI for Business Productivity online course, which is expected to launch this year, will offer participants the opportunity to learn the practical application of several AI tools to optimize various business functions guided by key learning objectives, including:

• Gain a good understanding of the different use cases and applications of AI in business, including marketing, customer service, sales, operations, HR, and innovation
• Learn how to identify the opportunities to adopt AI in your business
• Learn how to integrate AI tools into your business 
• Enhance your career prospects by acquiring in-demand skills in AI and demonstrating your ability to drive productivity and growth
• Connect and interact with a community of like-minded professionals, looking to deepen their knowledge in emerging technologies, as well as expand their network and career opportunities

Throughout the course, participants will get access to real-world case studies and examples showcasing successful applications of AI in numerous industries and business functions as well as interactive modules with practical exercises.

This course features several  lessons covering various topics and business functions, such as marketing, sales, operations, customer relations, and human resources. The modules consist of specific use cases for AI tools and hands-on training to ensure participants will learn how to integrate the tools into business functions, and the overall business operations.

The KPI Institute, with 19 years of experience in providing solutions for performance excellence, invites decision-makers, stakeholders, business owners, and entrepreneurs to future-proof their businesses and increase adaptability.

maentae’s goal is to empower individuals at every skill level to thrive in the dynamic and ever-changing modern workforce. Its core values focus on the combination of science, art and technology—crafting curricula that transcend boundaries with a harmonious blend of academic research and practical insights.

Participants who complete the course will be awarded a certificate in AI for Business Productivity, which they can use to prove their knowledge and proficiency in using AI to boost efficiency and productivity in business. Get updates on the launch of the course by visiting the TKI Marketplace, or contact Alexandru Muntean, head of customer engagement: [email protected] +40 747 060 997.

Big data now plays a crucial role in every business’ success. Through the application of analytics, data analysis is allowing businesses to become even more competitive. 

Organizations adopt big data and analytics to analyze massive volumes of data generated by offline and online trading. Based on the Big Data & Business Analytics Market Statistics 2030, the value of the global big data and business analytics market is estimated to increase to $684.12 billion by 2030 from $198.08 billion in 2020. 

The goal of data analysis is to extract meaningful information and use it to make informed business decisions. By analyzing and comparing previous and new data, organizations can understand what happened in between. Then, organizations can come up with metrics and action plans to drive their performance. It involves boosting customer loyalty, increasing sales, improving and retaining successful practices, and enhancing employee productivity.

According to a PwC poll of 1,000 corporate executives, data-driven firms were three times more likely to achieve big gains in their decision-making capabilities. 

A data-first approach is required for a digital-first enterprise strategy. In a multi-cloud context, a well-planned data strategy for a digital company gives “business transformation opportunities, cost reduction, better engagement, and maximum flexibility.”

To get the most out of data, organizations must create an effective data analysis process. This procedure entails objective setting, data collection, cleaning and analyzing data, and data visualization.

Before collecting data, defining the goals of the organization is important. Businesses can choose the type of data to collect and evaluate it to ensure it is aligned with their goals. Then, businesses must integrate data using tools such as Informatica PowerCenter, SQL Server Integration Services (SSIS) by Microsoft, AWS Glue by Amazon Web Services (AWS), and Alteryx Designer.. 

All data must be gathered in one place to be examined. Companies must clean their data by removing irrelevant and unwanted information, fixing structural errors, and filling out the missing data in order to produce accurate findings. To better understand the data, organizations should use data analysis software and other technologies. 

Some data analysis software available are XLSTAT, the leading data analysis and statistical solution for Microsoft Excel; Python, a powerful tool consisting of materials for any aspect of scientific computing; and SAS, a statistical software for business intelligence and data management.

To acquire useful insights, businesses should dive deep into the data. They should analyze and narrow down the results of the gathered data to draw conclusions. Then, organizations must interpret the results to figure out the best next steps to reach the goals established in the beginning of the process.

Organizations should deliver information in a readable and understandable format. Businesses can present data using graphs, maps, and charts. Data visualization can help companies compare data sets and observe their relationships.

Data analysis helps anticipate future trends more precisely, allowing organizations to determine where they are headed and what they need to get there.

To learn more about data analysis, explore The KPI Institute’s reports and free webinars and stay tuned for the next schedule of the Certified Data Analysis Live Online Course.