Know about Data science the rapid growing industry

Posted by DataTZ on Sunday, July 12, 2020 0

Data science

We live in the age of data. In the present day, data is all around us and collected at unprecedented levels. The amount of data that we generate is enormous. The growth rate is even more staggering, 90% of the world’s data was generated over the last ten years. Data is not very useful by itself unless it is converted into knowledge. This knowledge is in the form of insights, which can provide a lot of information about the underlying process. Corporations and Governments are increasingly becoming more data-driven: using insights from the data to drive their business decisions and future planning. Therefore, the methodology of extracting insights from data is called data science. Data science is known by different names including Statistics and data analytics.

What is Data?

Facts and statistics collected together for reference or analysis

There are different types of data which includes.

1.      Numerical include continuous and desecrate

2.      Categorical data

3.      Text data

4.       Image data

5.      Voice data.

6.       Video data

What is Big Data:

It involves the collection of large and complex datasets that are difficult to process using traditional data process applications. These data can be

1. Structured data- tables and data frames, etc.

2. Semi-structured data- in the forms of excel files, comma-separated files,

CSV, e-mails, etc.

3. Un-structured data- In the form of audio, video, images, log, chat, social

media posts, etc.

What are the sources of Big Data

• Social Networking Sites (Facebook, Twitter, Instagram, Tiktok, LinkedIn, etc.)

• Weather station

• Telecom Companies

• E-commerce sites-Amazon, Flipkart, etc.

• Banks and Insurance companies

Some Commonly used Data Science Terms

Note-It’s very common these days to come across the terms –

• Data Mining

• Data Analysis and Data Analytics

• Artificial Intelligence

• Machine Learning

• Deep Learning

   

What is Data Mining?

Data Mining is the analytic process designed to explore data (usually large amounts of data - typically business or market related) in search of consistent patterns/trends and/or systematic relationships between variables, and then to validate the findings by applying the detected

patterns to new subsets of data.

What is Data Analytics?

Data analytics is a process of exploring and analyzing large datasets in order to draw conclusions about the useful information they contain. In other words, Analytics is defined as the scientific process of transforming data into insights for making better decisions. Classification of Data Analytics:

1. Descriptive Analytics- What happened? (It provides a summary view of facts and figures and prepare data for the future analysis-past summary)

2. Diagnostic Analytics- Why did it happen? (to arrive at the source of the problem)

3. Predictive Analytics- What will happen? (to forecast trends based on the current outcome)

What is Machine learning?

(The ability for a computer to learn without being programmed)

Machine learning is a subfield of Artificial Intelligence (AI) that involved self-learning algorithms that derived knowledge from data in order to make predictions. Instead of requiring humans to manually derive rules and build models from analyzing large amounts of data, machine learning offers a more efficient alternative for capturing the knowledge in data to gradually improve the performance of predictive models and make data-driven decisions. It plays an important role in our everyday lives. Ex- Self-driving cars, email spam filtering, etc.

Types of machine Learning:

1. Supervised learning- (classifications such as Logistic regression)

2. Unsupervised learning- (Cluster analysis)