Question

1. SQL is considered one of the most valuable skills to empower managers as data analysts. Search the Web for free resources that teach SQL. Try a free introductory lesson (you might find these in sites like Khan Academy, and Code Academy, among others). Is this something you might continue to explore on your own? Does your university offer classes where you can learn SQL and other methods and technologies used in data analytics?

2. Name and define the terms that are supplanting discussions of decision support systems in the modern IS lexicon?

3. Think about the amount of data that is collected about you every day. Make a list of various technologies and information systems you engage with, and the organizations that use these technologies, systems, and services to learn more about you. Does this information serve you better as a consumer? What, if any, concerns does broad data collection leave you with?

4. What do you think about dynamic pricing? Is it good or bad for consumers? Is it good or bad for businesses? Explain your answer.

5. What is business intelligence? Provide examples of three types of business intelligence software used by firms to support managerial decision making.

Answer 1

Answer:-

1) SQL is not a programming language, it's a query language. The primary objective where SQL was created was to give the possibility to common people get interested data from database. ... So once you learn SQL it should be similar to work across any relational databases.

If you already have a career in computer programming or you are skilled in this area, learning the SQL basic could take as little as two to three weeks. However, if you need to take a beginner's computer programming course prior to learning the SQL language, it could take some additional time.

2) Increasingly standardized corporate data, and access to rich, third-party data sets—all leveraged by cheap, fast computing and easier-to-use software—are collectively enabling a new age of data-driven, fact-based decision making. The Two Most important new managerial Lexicon are

a) The phrase of the day is business intelligence (BI), a catchall term combining aspects of reporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis.

b) Alongside business intelligence in the new managerial lexicon is the phrase analytics, a term describing the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.

3) Collecting user data is common practice in modern websites and applications as a way of providing creators with more information to make decisions and create better experiences. Among other benefits, data can be used to help tailor content, drive product direction, and provide insight into problems in current implementations. Collecting relevant information and using it wisely can give organizations an edge over competitors and increase the impact of limited resources.

While data can help your organization fulfill its objectives, it is important to keep in mind that there are downsides to collecting and storing information about users. Privacy, security, ethical, and legal considerations can influence what type of data you collect, what you do with it, and your responsibilities to data owners. Failure to handle these concerns responsibly can result in significant financial and reputational damage, and potentially expose you to legal ramifications.

**Benefits of Collection of user data

a) Analyzing User Data for Product Development and Design

b) Creating Personalized Experiences and Reaching Relevant Audiences

c) to implement account recovery

d) providing context for existing data from other sources

e) for auditing purposes and for compliance with government requirements.

** Problems /Threats of collecting User Data

a) Data Collection Can Compromise Privacy

b) Data Collection Can Compromise Anonymity

c) Data Can Be Used for Discrimination

d) Data is Often Shared More Broadly than Users Intended

One consideration that people tend to oversimplify when considering collecting and storing data about their users is access control. Access control can mean making sure that outside parties cannot read the data you are collecting, but more broadly speaking, it can mean defining boundaries for anyone interacting with the data. For instance, this can mean cordoning off entry to employees whose functions are unrelated to the data, ensuring that vendors or partners cannot access it without informing users, and considering what it would mean to be asked for access from government agencies. Access to data is usually more complicated than initially expected.

4) Dynamic pricing, also referred to as surge pricing, demand pricing, or time-based pricing is a pricing strategy in which businesses set flexible prices for products or services based on current market demands.

** There are Up’s and Down’s related to dynamic pricing sometimes it is beneficial , sometimes it will not be for the businesses depending on the demand. The Best Example of dynamic Pricing is a “Uber”

Uber in particular is known for its use of dynamic pricing—price fluctuations driven by supply and demand. For example, on a rainy Saturday night, Uber may raise its fares because its drivers are in high demand and more consumers opt for car services over public transportation or a walk in the rain. Why is this not considered price gouging, you ask? Because Uber is transparent about their dynamic model—the app alerts users that the current rate is higher than usual, and by how much, giving the consumer the option to decline and find alternate means of transportation.

As Uber investor and board member have pointed out in their statements on Uber’s dynamic pricing model, this strategy is not new. Hotels, airlines, and rental car companies have long relied on dynamic pricing. This is why flight during the Thanksgiving holiday will cost more than a plane ticket purchased almost any other time of year.

**Dynamic pricing strategies can also sometimes benefit consumers and sometimes not.

Of course, dynamic pricing can benefit the consumer. The same pricing model that raises the rates on some days also allows hotels to offer last-minute deals to fill inventory. And in those cases, the consumer wins.

There is another aspect of dynamic pricing, however, that sometimes raises eyebrows. The recent report on price steering and price discrimination, citing research that shows how merchandisers and travel companies intentionally offer different users different products or prices based on factors such as previous purchases and clicks or whether the consumer is using a desktop, laptop, or a mobile device.

These pricing strategies can seem nefarious and risk driving knowing customers away. When dynamic pricing and price steering are conducted intelligently, however, they can serve to reward loyal customers, provide goods and services at a lower fee when the acquisition cost is lower, and help deliver a more personalized experience. Newer platform companies seeking to establish their own pricing model may want to opt for the long-term view and ask if their pricing strategy is beneficial for both their vendors and their customers.

5) BI(Business Intelligence) is a set of processes, architectures, and technologies that convert raw data into meaningful information that drives profitable business actions.It is a suite of software and services to transform data into actionable intelligence and knowledge. BI has a direct impact on organization's strategic, tactical and operational business decisions.

Business intelligence software is a set of tools used by companies to retrieve, analyze, and transform data into useful business insights. Examples of business intelligence tools include data visualization, data warehousing, dashboards, and reporting.

Best BI Software used by firms are (By Category)

SAP Crystal Reports	iDashboards	Sisense	Tableau
Chartio	Dundas	Oracle BI	InsightSquared
Alteryx	Segment	SAS	Domo
Jaspersoft	Geckoboard	Birst	GoodData

**Data Storage is First level of Business Intelligance Software

It is done through

a) Data Warehousing

b) Data Marts

c) Extract , Tranform and Load Software (ETL)

d) Hadoop

**Analyzing big data with business intelligence software:-

Regardless of whether businesses choose to store their data in a data warehouse or run queries on the source system, data analysis and the resulting insights make the field appealing to business users.The various tools of analysis are:-

a) Data mining

b) Data Analytics and business intelligence software, It uses Predictive Analysis which includes( Predictive Modelling, Descriptive modelling & Decision Analytics)

c) Natural Language Processing

**Reporting is also a key feature of Business intelligence

It is done through the undermentioned processes:-

a) Online Analytical Processing (OLAP)

b) Data Visualization

c) Dashboards

d) Alerts and Notifications