Business analytics involves using tools and techniques to solve business-related problems by using specific quantitative methods. It focuses on understanding the previous data of the business through statistical methods and then developing new insights for the future. In addition, business analytics focuses on prediction and interpretation.

In today’s world, data analysis is used in various industries ranging from digital advertisement to city planning, healthcare, transportation, and more. All these industries use data from their previous campaigns to gauge performanceforimproving future services.

The application of statistical techniques to describe, modularize and condense the big data and then to presentthis data—with the help of illustrated images, tables, graphs—to make meaningful and informed business-related decisions is dataanalysis. This systematic conclusion of data helps youunderstand and derive results while eliminating the unnecessary chaos created by the rest of the information.

Enormous amounts of data are generated every day. Organizing and understanding this data has become challenging. It requires efficient tools and techniques for organization and analysis. However, given countless choices in these tools, it can be difficult to separate good from bad.

Thisis where comparison websites come in.

At digitalsupermarket.com,you can compare prices and features of hundreds of tools that can assist in data and business analytics.

With a better understanding of data analysis and appropriate tools, you can make better business decisions and work toward achieving your goals.

Let’s look at some widely used tools and techniques for understanding the business analytics of any organization.

Tools Used in Business Analytics

The tools used for business analytics involve using a variety of software applications that help understand qualitative and quantitative data and help streamline it to make it easily presentable and understandable. Some basic tools used are;

SAS Business Analytics 

It is a programming language capable of understanding high-grade text analytics. This software allows users to identify and rectify unorganized text data into relevant information that helps analysts drive meaningful insights. SAS BA is loaded with a range of statistical tools, which help analyze large data sets in real-time. It also helps predict future business trends based on past data. It can also handle customer profiling and marketing analysis to predict customer behavior and optimize communications.

Excel

Excel is an age-old tool with compelling features. Additional plug-ins are installed from time to time to keep it updated. This versatile tool is used for handling and analyzing massive amounts of data.

Splunk 

Splunk is a widely used business analytics tool in small to medium industries. Although it was designed to only process machine log file data, over time, a set of new and useful features were added, which include various visualization options and a user-friendly web interface.

Tableau

The dynamic and cutting-edge capabilities of Tableau to analyze big data and understand unstructured text is commendable. This software has reliable statistical tools that enable users to carry out an in-depth analysis of social media networks andpredict patterns using current and past data.

Fine Report

The Fine Report is quite similar to Excel. It has a drag and drop operation, which helps design reports and a data decision analysis system. In addition, it can connect to several databases and provides a variety of dashboard templates and self-developed visual plug-in libraries.

QlikView

The patented technology and in-memory processing make QlikView a preferred tool for business analytics. It helps produce business analytics reports ultra-fast. It allows users to visualize connections among data using certain colors to represent related and non-related data.

Micro-Strategy

This business analytics software has superior capabilities to deal with unstructured text data hassle-free, which can further be analyzed using this software’s text analytics solutions. It enables users to visualize real-time trend forecasting using analytical and statistical techniques.

It is considered a first-rate business analytics tool as it allows users to create and share reports on any device from anywhere on earth.

R and Python

These are flexible programming languages. R and Python are used for statistical analysis like regression analysis and predictive analysis to seecustomer behavior. R and Python works on the same concepts that machine learning and artificial intelligence use.

Board

Board has industry-leading business analytics models which allow users to design intuitive and interactive business analytics reports. It is considered a highly-scalable business analytics platform that integrates the best business analytics tools and powerful statistical models. It can manage massive amounts of data. It also manipulates data to support accurate scenario analysis.

Techniques Used in Business Analytics

Depending upon the sizeand type of data, different techniques are used for data analysis. These techniques can be categorized as follows;

Statistical Techniques

• Regression Analysis

This analysis describes the relationship between a dependent variable and one or more independent variables. This model can be a ridge, logistic, linear, and more.

• Dispersion Analysis

Analysts use dispersion analysis to determine the variability of the factors under study. It helps detect the effect of individual factors on a specificset of data. Finally, it helps study the dispersion of data in the area where the data set is spread.

• Factor Analysis

Factor analysis helps you identify whetheror not a relationship exists between a set of variables. The patterns among the original variables are revealed by the process of factor analysis. It helps in clustering and classification procedures.

Machine Learning Techniques

• Decision Trees

As the name suggests, it is a tree-shaped model used to represent a regression model. It divides huge data sets into understandable sub-sets while linking them together in a related decision tree.

• Fuzzy Logic

This technique is based on a probability that helps handle the uncertainties in data mining techniques.

• Evolutionary Programming

This technique brings together several types of data analysis using evolutionary algorithms. It is considered a domain-independent technique, which helps explore search spaces and helps manage user interaction efficiently.

Graphical Techniques

• Pie Chart

Pie charts represent the proportion of different classifications. But it can only be used for a single series of data. However, a multi-layered pie chart can be used to represent data in different categories.

• Gauge

Gauge is a materialized chart. The pointer shows dimension and the scale shows the metric. Interval comparisons are best represented by Gauge charts.

• Map

1. Flow Map

It establishes a relation between inflow and outflow area, showing a line that connects the geometric centers of gravity of spatial elements. These dynamic flow lines help reduce visual clutter.

2. Point Map

It shows the geographical distribution of data in points on a geographical background. The same-sized points are meaningless for single data. When points become bubbles, it represents the size of the data in each region.

3. Regional Map

Color is used in regional maps to show value distribution over a map.

Wrapping Up

The key to running an efficient business in today’s world is data analysis. When starting a new venture or improving an already up and running business, analytics can help youmake informed decisions,excluding human biases from the results.

Data analytics tools and techniques have made business analytics easier, but they still have limitations. So make sure to choose a data analytics tool that is most in tune with your business’ scope.