Everything about Data Analytics to clear your confusion

Contain and analyse raw data thrown at you with an overwhelming velocity with some of the best and effective Data Analysis tools available to you.

What is Data Analytics?

Data Analytics is an assortment of applications that includes Business Intelligence, reporting, analytical processing, and advanced analytics.

Data Analysis tools are a type of these applications that help you to extract, cleanse and categorize data to obtain important information about your business and draw appropriate conclusions.

There are 3 different types of Data Analytics applications.

• Exploratory Data Analytics(EDA), which aims at identifying patterns and relationships in data. Basically, knowing what happened.
• Confirmatory Data Analytics(CDA), which applies statistical techniques to decide whether hypotheses about a particular data set are accurate or not- Why it happened.
• Advanced Data Analytics applications includes Data mining that involves sorting of large data sets, predictive analytics that predicts customer behaviour and machine learning that uses algorithms to churn out data quickly and accurately.

Data Analytics Techniques

Data Analytics is divided into Quantitative Data Analytics which uses quantifiable variables that can be compared or measured statistically. And Qualitative Data Analytics which focuses on understanding the content of non-numerical data like text, images, audio and video.

Quantitative Data Analytics includes

• Visual Analytics- by creating graphs or visuals to analyse data.
• Content Analytics-using colour coded themes and ideas to parse the textual data.
• Narrative Analytics-by analysing stories, feedback and ideas communicated by employees and customers.

Qualitative Data Analytics includes

• Business Experiments-which include experimental design and A/B testing
• Regression Analytics-for understanding the relationship between variables.
• Correlation Analytics-to determine the strength between the variables.
• Time series Analytics -to assess changes over time and predict future trends.

What do Data Analysis tools do for your business?

Data Analytics is optimally achieved via the various Data Analysis tools to boost your business performance in the following ways,

• They bring in more revenue for your business.
• They enhance operational efficiency.
• They help you understand marketing campaigns better and optimize them along with your services.
• They enable you to respond and adapt to changing market trends.
• They give a competitive edge over your rivals.

OpenRefine

This Data Analytics tool helps you clean your data for efficient analysis.

Advantages

• Cleanses and transforms messy data.
• Parses data from web services and adds it to the data sets.

Disadvantages

• It is not suitable for very large data sets and does not work well with Big Data.

The top Data Analysis Tools for your business success

Tableau Public

It is a simple and intuitive tool for Data Analytics.

Advantages

• You can publish interactive data visualizations on the web for free and can embed visualizations into blogs and webpages for sharing online.
• You don’t require high level programming skills to use the tool.

Disadvantages

• There is data size limitation
• Data is public

OpenRefine

This Data Analytics tool helps you clean your data for efficient analysis.

Advantages

• Cleanses and transforms messy data.
• Parses data from web services and adds it to the data sets.

Disadvantages

• It is not suitable for very large data sets and does not work well with Big Data.

KNIME

This tool for Data Analytics helps in manipulating and analysing data through visual programming.

Advantages

• You can just drag and drop connecting points between activities instead of writing blocks of code.
• It supports programming languages.

Disadvantages

• Data visualization is not up to the mark.

Google Fusion Tables

This Data Analysis tool is a larger version of Google Spreadsheets.

Advantages

• You can visualize data through a bigger table online.
• You can filter and summarize thousands of rows of data.
• You can merge tables with other data on the web

Disadvantages

• The total size of data you can send in one API call cannot be more than 1MB.
• It can include only the top 100,000 rows in the query results.

NodeXL

It is a free and one of the best Data Analytics and visualization tool in Excel.

Advantages

• Enables efficient data import.
• Graph visualization and analytics.
• Data representation.

Disadvantages

• You need to run data extractions at different times.
• May seeding terms are required for a single particular problem.

The other Data Analysis tools are Wolfram Alpha, Google Search Operators, Solver and Dataiku DSS, R Programming, Python, SAS, Apache Spark, RapidMiner, QlikView, GA 360, Adobe and Spunk.

Eye tracking is a Data Analytics technology that is now gaining popularity.

A computer that is fitted with an eye tracking can detect what the user is looking at and provide valuable insights into the gaze patterns of your website users. It consists of sensors as well as algorithms.

And Nabler is always ready with help with Data Analytics

Implementation Audit in Data Analytics

Get a comprehensive review of the quality of your data, implementation of your tracking codes, and the configuration of all your tools. Sit back while we do a health check of your website, deep dive into your data layer, do a detailed assessment of resources that are broken, and give recommendations in a Site Architecture Audit report that will serve as a schema for the Implementation process. We can also configure your Google Analytics with custom dimensions and help you take a holistic view of your analytics data, affording you greater visibility on important website metrics and areas for improvement.

Tag Implementation in Data Analytics

Our reliable Tag Management System gives you the freedom to add, modify or remove tags whenever necessary, reduce maintenance overheads across the board, and easily integrate third-party software into all your digital properties. You can also easily migrate from one tool to another without having to worry about losing historical data. And optimize your time, spend and effort by leveraging the tech stack to enable offline-online integration, and add value to your day-to-day operations.

Data Lake & Data Pipe

Get your very own window seat to an integrated view of customer data. Combine data sources for easy analysis, get a single view of the customer, add and delete data sources easily, and make your data a lot more reliable with a centralized data lake.

For more information please visit – our website or write to us at support@nabler.com

Organizations that don’t leverage the Data Analysis tools and techniques tend to fall apart because Data Analytics is the key to capture products that automatically glean and analyze data, deliver information and predictions. Know what is Data Analytics and steer yourself out of business calamities.