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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

What is business analytics? Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. The discipline is a key facet of the business analyst role. Business analytics techniques.

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Analytics Insights and Careers at the Speed of Data

Rocket-Powered Data Science

The vast scope of this digital transformation in dynamic business insights discovery from entities, events, and behaviors is on a scale that is almost incomprehensible. Traditional business analytics approaches (on laptops, in the cloud, or with static datasets) will not keep up with this growing tidal wave of dynamic data.

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Join me at Live! 360 Orlando to learn more about Applied Business Analytics

Jen Stirrup

360 Orlando and I’m presenting a workshop on From Business Intelligence to Business Analytics with the Microsoft Data Platform. Data becomes relevant for decision making when we start to use it properly, so this workshop will demonstrate the use of analytics for real-life use cases. Power BI and Marketing Data.

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The Role of Data Analytics in Football Performance

Smart Data Collective

Data analytics can impact the sports industry and a number of different ways. Sports leagues and teams are using analytics to estimate turn out at various sporting events, predict the performance of individual athletes, identify ways that athletes can improve their performance and improve marketing strategies.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics.

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A Guide To The Methods, Benefits & Problems of The Interpretation of Data

datapine

More often than not, it involves the use of statistical modeling such as standard deviation, mean and median. Let’s quickly review the most common statistical terms: Mean: a mean represents a numerical average for a set of responses. Standard deviation: this is another statistical term commonly appearing in quantitative analysis.

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PASS Financials: past, present and the Future:

Jen Stirrup

My analysis is based on the Financial statements put forward by PASS using some basic metrics; until you do that piece, you can’t move forward to compare and contrast it with other data since you have not done your ‘descriptive statistical analysis’ first to ensure that the comparison is valid. From 2014 onwards, I tried to do exactly that.

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