4 Types of Data Analytics to Boost your Business

We begin our series of publication about Big Data with an explanation of some basic principles. In this post, we’ll take a look at types of data analysis that can be implemented for your benefit.
These describe what has already happened.
With the help of descriptive analysis, any company is able to group its customers by social factors, behaviour and other features, as well as monitoring peak activities according to seasonal or local factors.
Descriptive analytics manipulates figures from multiple data sources to provide valuable information about the past. So, developers can predict important trends and signal the necessity of preventative or stimulative actions.
This type doesn’t simply state but aims to find the reason behind why something happened. We use it to identify the patterns and consequences of our policies and actions. It provides a deeper understanding of any given problem.
Predictive analytics address what might happen.
To be able to predict trends and see into the future, this type of analytics uses the results of the previous two – i.e. it bases its results on true facts of the past.
However, it’s important to understand that all the results this type of analytics provides you with are approximate. The accuracy of data and the stability of the situation have a significant influence on the result. It requires careful processing and constant optimisation.
Combining the approaches gives the best, most relevant results.
Prescriptive analysis is based on mathematical modelling. Its mission is to show the consequences of certain actions based on possible changes to data and conditions.
When is it time to use prescriptive analysis?
Predictive analytics help to collect the figures needed for informed decision-making, while prescriptive analysis constructs different solutions for you to choose from.
To provide true-to-life results, the combination of all four methods is the best option. The wide variety of information sources and compilation of different mathematical approaches to interpretation increase the accuracy and value of the results.
Data analytics in a business context helps to better recognise the dependencies and cardinal processes and provide key points for improvement based on probability rather than pure intuition.
We’ve collected several surveys to find out this fact.
McKinsey has published an e-book dedicated to the state of data analysis as for 2018. They declare its increasing importance for improved customer satisfaction.
BI-survey website names the most important data analytics trends for 2019.
These are:
The trends that evidently enjoy greater importance this year are agile BI development and advanced analytics tools. The less popular ones are related to real-time analytics and mobile BI. They appear to be less practically valuable when compared with diagnostic analytics and predictive analytics.
Here we share famous case studies of popular brands using big data analytics.
An interview with the company’s director of data strategy confirmed that the secret behind client retention for Coca-Cola is big data analytics.
Netflix uses big data analytics for targeted advertising. It has more than 100 million loyal clients and collects enormous amounts of data on a daily basis. By making successful suggestions as to what movie or series the user should watch next, they’ve become as addictive as cocaine.
Singapore-based UOB Bank applied data analytics to reduce risks. As such, the security of the whole institution depends on the accuracy and speed of data processing.
These are the most common dimensions of big data measurements. Variety refers to the number of data types, mentioned above, volume refers to the total amount of aggregated data, and velocity refers to the speed of data processing.
Some researches add another V: Variability. So, we got 4V.
Variability shows the data dispersion and is measured with the classical metrics of math statistics: range, variance and standard deviation.
By this link, you’ll find additional information about these factors.
Big data analysis creates advantages for the business owners by showing the not evident connections of courses and consequences.
This lead to improvement of the forecasting and planning, reduction of the pick loads and operative costs, and optimisation of the business flow.
With the help of IT experts who combine deep mathematical knowledge with advanced programming capabilities, your firm can realise productivity magnification and outstrip your competitors.
Read other materials about big data from our blog:
https://magora-systems.com/how-to-overcome-big-data-problems-in-ga/
https://magora-systems.com/big-data-analytics-in-real-time/
https://magora-systems.com/how-to-use-data-analytics-in-business/