Data Mining Question Paper tools and benefits

Introduction:

This tutorial is giving brief of Data Mining Question Paper tools and benefits.

We have included question papers from various universities so that one can have enough idea about field of data mining. Hope you will like this, if yes then please let us know in comments.

Question bank:
Comprehensive list of many question papers containing 100s of questions on data mining and warehousing with some solved question papers and links to many other question papers.

Definition:
Data mining is the systematic usage of sql and other coding skills to clean data, applying mathematics and statistical techniques to extract useful information and presenting that in easy to digest manner.

Why do we use Data Mining?

use of data analysis and data science
  • Extracting useful information:
    It is used to explore large datasets and getting useful information out of it using mathematics, statistics, visualisations tools, manually crunching that data on excel or Google Sheets.
    • For e.g. Suppose you have data of region wise sales data like account manager, sales amount, number of calls required to close the sale etc. then using the data you can find out in each region on an average how many calls are required to make a sale, who is the best account manager in each region etc.
  • Noise removal:
    Dataset can be related to anything like marketing, sales, business, user etc. Job of a person skilled in data mining is to get remove noise and extract useful information to impact business decisions out of the data.
    • For e.g. Suppose by fault text data is entered in the numerical column then any logic for calculation will not work unless you remove those text columns and vice-versa. So, data cleaning is another important step in data mining.
    • Or we can also say that for data analysts or data scientists having data processing and data cleaning skills is very much required.
  • Faster Insights Generation from Increasing dataset YoY:
    As the digital dataset is increasing at a very faster rate year over year and so requirement of this skill in every field is increasing day by day.
    • For e.g. As dataset increases it becomes practically impossible to visually check the data and so summarising that using SQL queries is required. So, data mining experts will write queries and summarise the results as per the requirement, hence avoids any manual effort.

How to get job in Data Mining field?

Common job titles:
Data Analyst post in software, IT, e-commerce, consulting etc. companies is the most common job in data mining field.

Ways to get job:
There are several ways to get job in this field viz. by doing internship during college in this field, doing online certification from online websites like coursera, linkedin etc. or doing degree from some college there are a lot of colleges who are offering courses in analytics field.

But as a data analyst having real business knowledge is very important for doing analysis. Understanding domain first will help in moving up later in your career.

Benefits of Using Data Mining:

  • Better Decisions:
    Decisions are backed by data hence reliability of decision increases,
    • For e.g. best region for sale, best product to sell, best time to sell the product, best person who can make the sale etc. are some questions that will come to your mind to increase your profitability and once you get insights that is backed by data your confidence and on ground results improves alot.
  • Better Prediction:
    Helps in prediction of risks, frauds etc. in finance companies like banks,
    • For e.g. it is used in fintech companies to predict price of stock, bonds etc. in future; predicting customer who may default based on their behaviour pattern etc.
  • Better Forecasting:
    Future forecasting based on trends observed in past data,
    • For e.g. Using time series forecasting to find effect of your increase in investment on business next year.

Tools | skills | coding language required for Data Mining in real jobs:

For data mining very few tools/ skills / coding language are required and are must for doing this, for e.g.:

  • SQL for querying database,
    • For summarising large datasets into certain number of data points,
    • select statements, insert, from, having, join etc. are must for understanding SQL better,
  • Python for data science or machine related stuff,
    • Using python scikit-learn library to apply different data science models like regression, classification, clustering etc. on data.
  • Knowledge of Visualisation Tools:
    For effective presentation of data using tools like Tableau, Qliksense, Datapine, Microsoft Power BI etc.
    • Extracting useful data and creating trend lines, bar charts etc. to show increasing or decreasing trends for a metric and then sharing it with other users in the company.
    • Depending on the budget and use case one can select the appropriate visualisation for their organisation.
  • Knowledge of Excel, Google Sheets for analysing datasets etc.
    • For small datasets / adhoc request it is preferred to use excel, Google Sheets etc. and in case some manual enrichment of data is require then it’s always good to go for excel or Google Sheets.
    • pivots, vlookup, sumifs, countifs, len, custom formulas etc. are must to know in Excel,
  • Statistics:
    • mean, median, mode, percentiles, outliers removal etc.
    • Regression techniques etc.
tools required for data mining

Data Mining Question Papers from Different Universities:

RGPV 8th Semester one full Solved Question Paper:

Snowflake overview, Data warehouse architecture, data cleaning and data transformation techniques and need etc. are explained very well.

VTU 6th Semester Data Mining and Data Warehouse Question Papers:

More theoretical and basic questions like what is date warehouse, tell us about clustering techniques etc.

Anna University Data Mining and Data Warehousing Question papers:

Big 25 page pdf document having MCA degree examination question papers many question papers from many years, but mainly theoretical questions only viz. what is data mining, date warehousing, data cube, data reduction techniques etc. to name a few topics.

Data Warehousing and Data Mining R13 Regulation B.Tech JNTUH-Hyderabad Old question papers from 2016-2018:

The question papers are for Jawaharlal Nehru Technical University, Hyderabad. The pdf of question papers are hosted online as well as these are downloadable as well.

Questions are again theoretical mostly asking for basic definitions related to data mining concepts viz. data classification, outliers detection, association rules, data preprocessing etc.

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY – Data Mining and Warehousing Question Papers:

Question papers from 2019 and 2020. Although, these are just unsolved question papers.

Final Words:

Except 1st one all the question papers are unsolved ones to give one an idea how questions vary from university to university, do let us know if you want us to help you with any of these questions we will more than happy to answer that.

I hope this article Data Mining Question Paper has provided you some value, if your answer is no then please let us know what we can do to improve the quality of content we will try our best to get the relevant information for you.

FAQs on Data Mining Question Paper tools and benefits:

Q. Why data mining is bad | side effects of data mining ?

Ans. If data is used for constructive purpose then data mining is a good thing, on the other hand if data is used to bring harm to people like for e.g. using their personal information for private benefits like disclosing their payment information or in any other way that leads to their loss in any terms then it’s not a good thing.

And this is the reason Europe has GDPR policy in place, which restricts any business from sending any promotional emails to their users without their consent and restricts them from using their information.

Q. Is data mining easy or hard?

Ans. According to task at hand it can be very easy to easy to hard to very hard, so there is no straight forward answer to it. But, again several factors which decides whether a task is easy or hard in data mining are:
– Data availability i.e. data is available or not,
– Data quality: If data has too much noise or errors which needs cleaning, then it increases effort of data mining as working on such data first requires data cleaning and transformation for running model or effective representation of data,
– Complexity of questions one is trying to answer using data mining: So, if question is quite complex and needs very deep insights then the data mining task in this case becomes hard.

Data Mining Question Paper tools and benefits contd.

Q. What are the common job titles associated with data mining? | Common job titles of data mining field.

Ans. Data Analyst, Data Scientist, Machine Learning Engineer, Data Engineer etc.

All, these are sort of very close job titles with slight variation in their job functions.

But, all these jobs have overlaps in terms of skills required like data mining, data cleaning, data transformation and making good story out of the data.

Q. Common used tools | skills | coding languages for data mining?

Ans. Excel, Google Sheets, Tableau, SQL, Python, PowerBI etc. to name a few are common used tools for data mining.

We have already explained in somewhat detail the usage of each one of them.

Hope this article “Data Mining Question Paper tools and benefits” is of use for you.

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