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Digital Thinking & Innovation > Unit 7 : Innovation through Analytics > Flashcards

Unit 7 : Innovation through Analytics Flashcards

1
Q

What is data?

A
  1. Is raw, unorganized facts that need to be processed
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2
Q

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

A
  1. Information
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3
Q

What is the characteristics of data?

A
  1. Simple and seemingly random
  2. Useless until it is organized
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4
Q

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

A
  1. The data being generated from large-scale enterprises
  2. The data generated from an individual
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5
Q

What is data analytics mean?

A
  1. Analyzing raw data in order to make conclusions about that information, to enhance productivity and business gain
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6
Q

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

A
  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
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7
Q

List out the examples of data analytics ( 4 )

A
  1. Fraud Management Report
  2. Live Tracking Report
  3. Sales Report and Future Target
  4. Google Analytics Report
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8
Q

Where is fraud management report generally used in?

A

1.Banking

  • Find the fraud transactions, hacking, unauthorized access to the account and so on
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9
Q

Where is live tracking report generally used in?

A
  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
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10
Q

Where is sales report and future target generally used in?

A
  1. All sectors to analyze their sales, revenues, and needs of customers
  • And also used to determine the future target and so on
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11
Q

What can we get from google analytics report ?

A
  1. User visit counts, location, device
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12
Q

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

A
  1. Gather Hidden Insights
  2. Generate Reports
  3. Perform Market Analysis
  4. Improve Business Requirement
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13
Q

Explain more on gather hidden insights

A
  1. Hidden insights from data are gathered and then analyzed with respect to business requirements
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14
Q

Explain more on generate reports?

A
  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
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15
Q

Explain more on perform market analysis

A
  1. Market Analysis can be performed to understand the strengths and the weaknesses of competitiors
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16
Q

Explain more on improve business requirement

A
  1. Alaysis of data allows improving business to customer requirements and experience
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17
Q

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

A
  1. Data Analyst
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18
Q

What does data analysts translate numbers into?

A
  1. Plain English
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19
Q

What are the skills required by Data Analyst?

A
  1. Statistic
  2. Data Collection
  3. Data Cleaning
  4. Data Analysis
  5. Hidden Insights Discovery
  6. Data Visualization
  7. Reports Generating
  8. Machine Learning
20
Q

What does big data mean?

A
  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
21
Q

What is the difference between big data and data analytics

A
  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
22
Q

What does big data analytics means?

A
  1. Complex process of examining large and varied data sets, to uncover information that can help organizations make informed business decisions
23
Q

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

A
  1. Format
  2. Storage
  3. Seachability
  4. Data Sizes
  5. Examples
24
Q

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

A
  1. R Programming
  2. Python
25
Q

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 ?

A
  1. Tableau Public
26
Q

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?

A
  1. QlikView
27
Q

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

A
  1. SAS
28
Q

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.

A
  1. OpenRefine/GoogleRefine
29
Q

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

A
  1. Microsoft Excel
30
Q

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.

A
  1. RapidMiner
31
Q

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?

A
  1. Konstanz Information Miner ( KNIME )
32
Q

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

A
  1. Apache Spark
33
Q

List out the 4 types of big data analytics

A
  1. Descriptive
  2. Diagnostic
  3. Predictive
  4. Prescriptive
34
Q

What does descriptive mean in big data analytics?

A
  1. Allows organizations to learn from past behaviors, and help them in understanding how they moght influence future outcomes
35
Q

What is the question for descriptive?

A
  1. What has happened?
  • How many cars did we sell last year?
36
Q

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

A
  1. Referred to as root cause analysis
  2. It provides deeper analysis to answer the questions
37
Q

What is the question for descriptive?

A
  1. Why did this happen?
  • Why did we only see x cars last year?
38
Q

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

A
  1. Uses this historical data, combined with customer insight, to predict future events
39
Q

What is the question for predictive?

A
  1. What will happen if …. ?
  • If I run x advertising programs, how many cars can we sell?
40
Q

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

A
  1. Uses AI to understand what the impact is of future decisions and uses those scenarios to determine the best outcome
41
Q

What is the question for descriptive?

A
  1. What should we do about this?
  • What do we need to do to sell x number of cars?
42
Q

List out the use cases of Big Data Analytics

A
  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
43
Q

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

A
  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
44
Q

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

A
  1. Netflixuses 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.
45
Q

Give example on big data analytics for risk management

A
  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
46
Q

Give example on driver of innovations and product development

A
  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.
47
Q
A

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