Advanced Analytics

Advanced Analytics is the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations.

Data is a powerful tool that’s available to organizations at a staggering scale. When harnessed correctly, it has the potential to drive decision-making, impact strategy formulation, and improve organizational performance.

WHAT IS DATA ANALYTICS IN BUSINESS?

Data analytics is the practice of examining data to answer questions, identify trends, and extract insights. When data analytics is used in business, it’s often called business analytics.

We use tools, frameworks, and software to analyze data, such as Microsoft Excel and Power BI, Google Charts, Data Wrapper, Infogram, Tableau, and Zoho Analytics. These helps us examine data from different angles and create visualizations that illuminate the story you’re trying to tell.

Algorithms and machine learning also fall into the data analytics field and can be used to gather, sort, and analyze data at a higher volume and faster pace than humans can. Writing algorithms is a more advanced data analytics skill, but you don’t need deep knowledge of coding and statistical modeling to experience the benefits of data-driven decision-making.

WHO NEEDS DATA ANALYTICS?

Any business professional who makes decisions needs foundational data analytics knowledge. Access to data is more common than ever. If you formulate strategies and make decisions without considering the data you have access to, you could miss major opportunities or red flags that it communicates.

Professionals who can benefit from data analytics skills include:

  • Marketers, who utilize customer data, industry trends, and performance data from past campaigns to plan marketing strategies
  • Product managers, who analyze market, industry, and user data to improve their companies’ products
  • Finance professionals, who use historical performance data and industry trends to forecast their companies’ financial trajectories
  • Human resources and diversity, equity, and inclusion professionals, who gain insights into employees’ opinions, motivations, and behaviors and pair it with industry trend data to make meaningful changes within their organizations

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