An Introduction to Data, Analytics & Insights

An Introduction to Data, Analytics & Insights

You don’t need us to tell you that data is digital information of characters, numbers, images or other methods of recording. This pool of data insights can be accessed to make decisions about specific actions. Data doesn’t have value unless it’s processed and analyzed in a precise manner. In this digital era, smartphones and the internet create several data points that need to be collected, curated, organized, and analysed. This potentially business-boosting big-data information can give insights to businesses only with appropriate data analysis, which will be discussed further in this article. Before we proceed, let’s understand the different types of data.

Types of data

We know that not all data can be considered the same when used for analysis. To simplify the process, data can broadly be divided in two categories:

Qualitative data

A non-numerical information that is observed, recorded and collected falls under qualitative data. An example of it can be a cake – its colour and taste.

Quantitative data

Data comprising numbers or data sets with numerical values and different parameters falls under the quantitative category.

Types of Data Analytics

Simplistically, data analytics can be divided into two categories…

Qualitative data analytics

Data analysis with qualitative information constitutes images, texts, documents, audio and recorded observations, transcripts and many more.. A qualitative researcher uses theoretical processes related to inductive reasoning. Through this manual process, s/he can interpret subjective meanings and generate hypotheses relevant for a specific business.

Quantitative data analytics

A quantitative data specialist has to go through three distinct stages to derive rational meaning from unstructured data. Quantitative data analysis can be conducted through the following three steps:

Step 1: Validating data

This is done via unprejudiced observation with a set of pre-requisite standards. S/he has to ensure whether the data collection procedure is followed correctly; and that the respondents chosen are relevant to the research and confirm completion of required tasks.

Step 2: Editing data

In this step, the quantitative researcher has to ensure the data sets used do not impede the accuracy of the outcomes.

Step 3: Coding data

This is the final step in quantitative data analytics, where the specialist has to prepare data by grouping and assigning values. For instance, s/he interviews 500 people of different ages for a specific product. The researcher will create and code different categories including 15- 20 years age bucket, 18 to 35 years age bucket and so on.

Characteristics of Big Data

Big Data is a huge volume of complex information that is generated by a company at a large scale and is extensively used to uncover the hidden data insights. Considered the pinnacle of Software Engineering, Big Data is purely designed to handle enormous data, generated every second. All the 5 Vs that we will discuss below, will be interconnected to the remarkable potential of Big Data.

  • Volume determines whether the particular data size can be used for Big Data.

  • Velocity refers to how fast the data is created and processed.

  • Variety refers to the nature of data, which can be structured or unstructured.

  • Veracity refers to the inconsistencies of data.

  • Value signifies what bulk of data can be used profitably.

Why Make a Career in Data?

Data research has extensive scope across various industries. With a certification in data, you can land several in-demand jobs such as

Data Scientist

Large Fintech & Tech enterprises are realising the potential of big data. To have expertise in this field can help boost your career. An average annual salary of this profession is estimated at $135,000 which is definitely a great compensation.

Business Intelligence Analyst

BIA’s recommendations are in high demand amongst eCommerce and healthcare organisations as they are able to make profitable decisions based on these analysts’ expert opinions. The average annual salary of BIA is estimated at $110,000.

Data Developer

A data developer has an indispensable value in an organisation’s development team. As per the U.S reports, the annual salary of a developer is around $98,415.

Best Big Data Certification Courses in India

Simply put, a certification in Big Data can increase your likelihood to boost your career and get hired by tech giants. If you are planning to make a career in data, you can easily choose a programme with us, at Xebia Academy. We offer over 30 courses on Big Data across various categories.

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