16 November 2018
Data Analytics – the process of analysing data sets – enables organisations to make better-informed decisions. It’s a key focus in many businesses today, and covers a range of techniques and technologies including Business Intelligence (BI), Predictive Analytics, Machine Learning (ML) and Big Data Analytics.
Let’s explore these in more detail, and look at their practical usage in a business environment.
BI is the process of analysing and presenting data from multiple sources, to help managers and executives understand what’s happening in their business. A number of BI software tools – including Power BI and Tableau – are available, with typical users being business analysts, financial analysts, data scientists and other staff across the business.
The BI process involves:
The main point of BI is that the wealth of available data in an organisation is transformed into information and insights that are easy to understand – and can be acted upon. It’s used extensively in a wide range of industries and departments/functions. Example of usage include:
Any organisation or department that has metrics or KPIs – in any sector – will benefit from applying BI techniques.
While BI tends to look at historical data, advanced analytics focuses on forecasting and predicting future events. It’s a range of techniques that include Predictive Analytics, Machine Learning (ML) and Big Data Analytics.
As with BI, the Predictive Analytics process involves accessing data from multiple sources, cleaning and shaping it, and then analysing it for useful information and insights. Predictive Analytics, though, also involves the use of statistical analysis and automated ML algorithms to create predictive models.
These models give a probability score on the likelihood of a particular event occurring – and as additional data becomes available, the algorithms validate or revise the model. It’s a self-learning process that identifies data patterns and makes predictions, which get more accurate over time. Machine Learning allows advanced analytics to be performed on massive, complex data sets (Big Data Analytics) in real-time.
A wide range of sectors and functions use advanced analytics to examine data, perform ‘what if’ analyses and predict likely scenarios. Examples of usage include:
Here at JBI Training, we provide a range of Data Analytics training courses for data scientist, data analysts, business analysts, financial analysts, other business users and software developers. Courses include:
See our Power BI training course (2 days) where you learn the fundamentals of this popular set of Microsoft Business Intelligence tools –
See our Tableau training course (2 days) where you learn to create reports and dashboards from Excel, SQL server and other databases –
See our Python Machine Learning training course (3 days) where you learn Python Machine Learning skills for Predictive Analytics –
See our full range of Analytics training courses here http://www.jbinternational.co.uk/courses/analytics
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