Unit 7 : Innovation through Analytics

Question 1

What is data?

Answer 1

1. Is raw, unorganized facts that need to be processed

Question 2

What is called as when data is processed, organized, structured or presented in a given context to make it useful

Answer 2

1. Information

Question 3

What is the characteristics of data?

Answer 3

1. Simple and seemingly random
2. Useless until it is organized

Question 4

How does organization benefit from the data collected? ( 2 )

Answer 4

1. The data being generated from large-scale enterprises
2. The data generated from an individual

Question 5

What is data analytics mean?

Answer 5

1. Analyzing raw data in order to make conclusions about that information, to enhance productivity and business gain

Question 6

What does extracted data needed to analyze different behavioral patterns ? ( 2 )

Answer 6

1. Clean
2. Categorized

• Tools used vary according to the organization or individual
• Processes of data analytics have been automated into mechanical processes and algoithms that work over raw data for human consumption

Question 7

List out the examples of data analytics ( 4 )

Answer 7

1. Fraud Management Report
2. Live Tracking Report
3. Sales Report and Future Target
4. Google Analytics Report

Question 8

Where is fraud management report generally used in?

Answer 8

1.Banking

• Find the fraud transactions, hacking, unauthorized access to the account and so on

Question 9

Where is live tracking report generally used in?

Answer 9

1. Transport Sectors ( Meru , Ola, Uber )

• Track the vehicles, customers’s requests, payment management, emergency alert and to find the daily needs and revenues and so on

Question 10

Where is sales report and future target generally used in?

Answer 10

1. All sectors to analyze their sales, revenues, and needs of customers

• And also used to determine the future target and so on

Question 11

What can we get from google analytics report ?

Answer 11

1. User visit counts, location, device

Question 12

List out the 4 main factors which signify the need for Data Analytics

Answer 12

1. Gather Hidden Insights
2. Generate Reports
3. Perform Market Analysis
4. Improve Business Requirement

Question 13

Explain more on gather hidden insights

Answer 13

1. Hidden insights from data are gathered and then analyzed with respect to business requirements

Question 14

Explain more on generate reports?

Answer 14

1. Reports are generated from the data and passes on to the respective teams and individuals to deal with further actions for a high rise in business

Question 15

Explain more on perform market analysis

Answer 15

1. Market Analysis can be performed to understand the strengths and the weaknesses of competitiors

Question 16

Explain more on improve business requirement

Answer 16

1. Alaysis of data allows improving business to customer requirements and experience

Question 17

Who can analyze data by applying various tool and techniques and gathering the required insights?

Answer 17

1. Data Analyst

Question 18

What does data analysts translate numbers into?

Answer 18

1. Plain English

Question 19

What are the skills required by Data Analyst?

Answer 19

1. Statistic
2. Data Collection
3. Data Cleaning
4. Data Analysis
5. Hidden Insights Discovery
6. Data Visualization
7. Reports Generating
8. Machine Learning

Question 20

What does big data mean?

Answer 20

1. A concept in Software Engineering which we use when we have a large sets of machine generated data, which in most of the cases in unstructured and not easy to use with traditional RDBMS concepts

Question 21

What is the difference between big data and data analytics

Answer 21

1. Data analytics are more of analyzing data which could be structured or unstructured
2. While big data in most cases is unstructured and not easy to use with traditional RDBMS concepts

Question 22

What does big data analytics means?

Answer 22

1. Complex process of examining large and varied data sets, to uncover information that can help organizations make informed business decisions

Question 23

What factor do we compete between structured and unstructed data? ( 5 )

Answer 23

1. Format
2. Storage
3. Seachability
4. Data Sizes
5. Examples

Question 24

List out the programming language for the below statement :
1. Leading analytics tool used for statistics and data modeling
2. Provide various machine learning and visualization libraries such as Scikit-Learn, TensorFlow, Matplotlib, Pandas, Keras

Answer 24

1. R Programming
2. Python

Question 25

What is a free software that connects to any date source such as Excel, corporate Data Warehouse etc, then creates visulations, maps, dashboards etc with real-time updates on the web ?

Answer 25

1. Tableau Public

Question 26

What tool offers in-memory data processing with the results delivered to the end-users quickly. It also offers data association and data visualization with data being compressed to almost 10% of its original size?

Answer 26

1. QlikView

Question 27

What is a programming language and environment for data manipulation and analytics, this tool is easily accessible and can analyze date from different sources

Answer 27

1. SAS

Question 28

What is a data cleaning software that will clean up data for analysis. It is used for cleaning messy data, the transformation of data and parsing data from websites.

Answer 28

1. OpenRefine/GoogleRefine

Question 29

What tool is is one of the most widely used tools for data analytics. Mostly used for clients’ internal data, this tool analyzes the tasks that summarize the data with a preview of pivot tables ?

Answer 29

1. Microsoft Excel

Question 30

What is a powerful, integrated platform that can integrate with any data source types such as Access, Excel, Microsoft SQL, Tera data, Oracle, Sybase etc. This tool is mostly used for predictive analytics, such as data mining, text analytics, machine learning.

Answer 30

1. RapidMiner

Question 31

What is a open-source data analytics platform, which allows you to analyze and model data. It provides a platform for reporting and integration through its modular data pipeline concept?

Answer 31

1. Konstanz Information Miner ( KNIME )

Question 32

What is one of the largest large-scale data processing engine? * It executes applications in Hadoop clusters 100 times faster in memory and 10 times faster on disk. Popular for data pipelines and machine learning model development

Answer 32

1. Apache Spark

Question 33

List out the 4 types of big data analytics

Answer 33

1. Descriptive 2. Diagnostic 3. Predictive 4. Prescriptive

Question 34

What does descriptive mean in big data analytics?

Answer 34

1. Allows organizations to learn from past behaviors, and help them in understanding how they moght influence future outcomes

Question 35

What is the question for descriptive?

Answer 35

1. What has happened? * How many cars did we sell last year?

Question 36

What does diagnostic mean in big data analytics? ( 2 )

Answer 36

1. Referred to as root cause analysis 2. It provides deeper analysis to answer the questions

Question 37

What is the question for descriptive?

Answer 37

1. Why did this happen? * Why did we only see x cars last year?

Question 38

What does predictive uses in big data analytics? ( 2 )

Answer 38

1. Uses this historical data, combined with customer insight, to predict future events

Question 39

What is the question for predictive?

Answer 39

1. What will happen if .... ? * If I run x advertising programs, how many cars can we sell?

Question 40

What does prescriptive uses in big data analytics? ( 2 )

Answer 40

1. Uses AI to understand what the impact is of future decisions and uses those scenarios to determine the best outcome

Question 41

What is the question for descriptive?

Answer 41

1. What should we do about this? * What do we need to do to sell x number of cars?

Question 42

List out the use cases of Big Data Analytics

Answer 42

1. Using Big Data Analytics to Boost Customer Acquisition and Retention 2. Use of Big Data Analytics to Solve Advertisers Problem and Offer Marketing Insights 3. Big Data Analytics for Risk Management 4. Big Date Analytics as a Drive of Innovations and Product Development 5. Use of Big Date in Supply Chain Management

Question 43

Give example on big data analytics to boost customer acquisition and retention

Answer 43

1. In the year 2015, Coca-Cola managed to strengthen its data strategy by building a digital-led loyalty program. 2. Coca-Cola director of data strategy was interviewed by ADMA managing editor. The interview made it clear that big data analytics is strongly behind customer retention at Coca-Cola

Question 44

Give example on big data analytics to boost advertisers problem and offer marketing insights

Answer 44

1. Netflix uses big data analytics for targeted advertising 2. Netflix sends subscriber suggestions of the next movie to watch based the past search and watch data. This data is used to give them insights on what interests the subscriber most. 

Question 45

Give example on big data analytics for risk management

Answer 45

1. UOB bank tested a risk management system that is based on big data. 2. The big data risk management system enables the bank to reduce the calculation time of the value at risk. - It would initially take about 18 hours - With the risk management system that uses big data, it only takes a few minutes. 3. Through this initiative, the bank will possibly be able to carry out real-time risk analysis in the near future

Question 46

Give example on driver of innovations and product development

Answer 46

1. Amazon Fresh and Whole Foods 2. The data-driven logistics gives Amazon the required expertise to enable creation and achievement of greater value. 3. Amazon whole foods is able to understand how customers buy groceries and how suppliers interact with the grocer.