BUS611: Data Management

Data is a valuable resource. Therefore, data management has become an important administrative function. An effective data management plan should govern how to acquire, store, and secure organizational data. Remember, reliable data management plans depend on your ability to identify the value added to operational and strategic planning.

Read this chapter. Focus on the differences between data, information, and knowledge; why database technology for data resource management is important; and the role of database management systems. Answer the study questions at the end of the chapter. Why is data management valuable to the success of an organization? What are some common weaknesses in data resource management? How can they be mitigated?

Read this lesson. Pay attention to the lifecycle (process) of data sets. Answer the questions in this lesson. 

Data lifecycle management (DLM) is the policy or process that governs organizational data use. You learned that data management is an administrative function and DLM is a process to manage and preserve that data. Remember, good DLM includes all the phases of the data lifecycle. This is essential to data-driven decisions and actions taken by organizations daily.

Data is collected, stored, and shared throughout every department within an organization. Data is continuously shared and verified in order to reveal new events and predict outcomes. Data governance provides the framework to improve data management and sharing. This continuous framework evaluates data by establishing a data lifecycle.

Watch this webinar, and pay attention to data governance in relation to a continuous process, improving data quality, and the benefits of governing data. What are potential pitfalls if no one is responsible for governing data? What steps can you apply to ensure data governance is successful? How would you apply data governance with an organizational process model?

Watch this video on managing research data. Focus on the risks associated with not managing research data, the importance of sharing research data, and the challenges of both sharing and managing research data.

Research data is collected and stored daily in various forms. Because data is a valuable resource, it requires proper management and sharing between organizations. Remember, data management ensures reliable information and protects the integrity of data within your organization. Be sure you have a detailed plan on how to manage research data.

Watch this video on the basics of research data management. Use what you learned about the importance and challenges of sharing and managing data to follow the data lifecycle in the video. Where can you locate relevant standards for managing research data? Why is it important for data to be as available as possible? What are the benefits of dataset licensing?

Watch this video on DMP. Pay attention to the definition, questions that develop a DMP, and content that make up a DMP. Remember, you will more likely share research data. Therefore, take notes on the advantages of a good data management plan.

Study the Data Management Plans section of the US Geological Survey. Notice the templates and examples that are provided. How would you evaluate these data management plans? How could you apply one of the templates to develop your own DMP for a situation from your professional experience?

Now that you can describe and explain DMP, let's cover a few careers within the data management field.

Watch this webinar on the evolving role of the data architect. Pay attention to the opportunities that exist for data professionals working for data-driven organizations. Take note of the various organizations that utilize data for improvement and transformation. 

Read this summary report for data consultants/architects. Familiarize yourself with the knowledge, skills, abilities, and education level organizations look for when seeking to hire a data consultant.

Read this summary report for operations analysts. Familiarize yourself with the knowledge, skills, abilities, and education level organizations look for when seeking to hire operations analysts.

Read this summary report for an IT Systems analyst. Familiarize yourself with the knowledge, skills, abilities, and education level organizations look for when seeking to hire IT systems analysts.

Read this summary report for DBAs. Familiarize yourself with the knowledge, skills, abilities, and education level organizations look for when seeking to hire database administrators. 

Remember, proper data management and data lifecycle management add value to any organization. It is becoming easier to share and manage data due to advancements in technology. Therefore, it is important to have data management and data lifecycle management processes. This produces integrity in standards that effectively collect, analyze, and share data.

Read this chapter. Pay attention to the properties of a database and DBMS. Then, complete the exercise at the end of the chapter.

Read this chapter and focus on the advantages of each of the database characteristics. Remember to take notes on the "key terms". Then, complete the exercises at the end of each chapter to evaluate what you have learned about the use of various database tools.

Recall the summary report on database administrators that you read earlier in Unit 1 (1.3.4). Pay attention to the tasks, skills, knowledge, and abilities. What is the importance of a DBA? What are some strengths and weaknesses of organizations that do and do not have DBAs?

Watch this video. Pay attention to the principal components of DBMS. Use what you learned and compare the components of DBMS. Why are the components essential to developing a DBMS? How would you justify why DBMS components are necessary for data-driven decision-making?

Watch this video on combining data management with organizational change. Pay attention to the process model and focus on how the presenter applied a data governance framework. Take notes on how each department utilized data to measure objectives and performance.

Watch this video. Data modeling makes analysis easier. For example, if you needed to compare data from the customer perspective and organizational objectives. It would be exceedingly difficult to conduct this type of analysis with a single query. However, this identifies the importance of data models before conducting data analysis.

Conceptual, logical, and physical data models are methods used to model data in a domain. While each of these is considered a data model, they are created for different purposes. Now, you will learn more about these data models and how to use them.

Watch this webinar on data modeling and metadata management. Pay attention to the purpose of data models, metadata, and relational databases. Do data models provide metadata management? Why or why not?

Read this chapter and learn the models listed in order of decreasing level of abstraction. Pay attention to the summary given on conceptual models. Complete the exercises at the end of the chapter.

Watch this video on the first steps of logical data modeling. Logical data modeling involves taking some construct, or data, from the physical world and representing it in a logical data model. The first step in logical data modeling involves identifying the data elements we want to represent and how they are related to each other via key fields.

Watch this video on Entity-Relationship (E-R or sometimes E/R) modeling. E-R models represent the first step in converting a conceptual data model into a physical data model.

Watch this video on data modeling that compares E-R modeling to UML modeling. Pay attention to each presenter as they discuss the pros and cons of each of these database modeling techniques.

Watch this video on the advantages of a relational model. Did you understand the advantages of logical and physical data models?

After completing this section, you should be able to explain the advantages and disadvantages of data models. Next, we will explain the E-R model and business rules.

Read this chapter and pay attention to the main concepts, kinds of entities, types of attributes, and types of keys. Take notes on the three relationship types and complete the exercise at the end of the chapter.

Watch this video on business rules. What is the relationship between E-R models and business rules? Are business rules important to E-R modeling? Why or why not?

Watch this lecture on the Enhanced E-R model. Take notes on the definition of supertype and subtype. Pay attention to the unique relationship between supertypes and subtypes.

Read this chapter and pay attention to the section on business rules and how they are obtained from users. Take note of the business rule examples and answer the exercises at the end of the chapter.

Watch this lecture and take notes on the security concepts discussed. Note the many different security threats that database management systems may be subjected to and the actions that the database administrator can take to mitigate against some of these threats. In particular, make note of the use of SQL injection attacks as you study SQL later in the course.

Remember, data models not only provide a basis for the design of a computerized database system, they are also very useful for communicating with non-technical business users. Business process owners work with data modelers in order to ensure that the database system being developed will meet the needs of the organization. The data model provides a common point of reference in the development process. As a data professional, you will have to create and structure database tables to support business operations and processes. In conclusion, you learned about various data models, their advantages, and their disadvantages. Now, you can explain data models and apply E-R models using the practical exercises given in this section.

Read this article and focus on the definition, types of data considered big data, and how to analyze it. Then take notes on the tools currently used to analyze big data.

Technology continues to advance an organization's ability to collect data. Next, you will learn about storing and making big data accessible by developing the infrastructure.

Watch this video on the infrastructure for big data and pay attention to the discussion on analytical models. Then take notes on the different types of big data systems used in the business world.

Big data storage is used to enable easy access to large amounts of data. You learned the importance of big data infrastructure. In this next section, you will learn about the role of big data storage for data analytics.

Read this article and pay attention to the four ways to process data, how big data analytics are used, and the methodology.

Read this article. What are the main challenges of using big data?

Read this article about the healthcare sector. Compare and contrast the challenges associated with each industry.

Read this article. Review the introduction to cloud computing and take notes on the aim and purpose of cloud computing. Then read the remainder of the article to become familiar with cloud-based services.

Keep in mind that cloud-based services can adapt or grow to meet the needs of the user. Service providers can deliver hardware and software based on organization needs. One benefit is that there is no need for organizations to own or allocate resources toward Information Technology (IT) staff.

Watch this video on cloud computing and business expectations. Pay attention to cloud computing and the future of IT. Take notes on the comparison between "old" computing and "cloud" computing. Listen to the examples given for each industry.

Read these sections to familiarize yourself with disaster recovery. Pay attention to the review of cloud computing and disaster recovery plans, and list the challenges associated with disaster recovery. Finally, compile a list of the different types of disaster recovery platforms.

Organizations that use cloud-based services can backup and store data in a virtual location. You learned that storing data in the cloud creates a faster and more agile organization. Think back to the list you made about the challenges associated with disaster recovery. Use what you learned about those challenges as you read this article and begin this next section.

Watch this video on minimizing risk in the cloud environment. Compare the challenges mentioned in this video with the list you made in the previous section. What were some common challenges that the organizations in this video faced? Why are data breaches and leaks a result of poor security?

Watch this tutorial about SQL. Pay attention and take notes on the introduction to SQL. Stop the video at 6:35. The remainder of this video describes the installation, configuration, and operation of MySQL. MySQL is an RDBMS that is in widespread use. MySQL is open source, meaning that it is free to download and use. We will cover the basics of MySQL in section 5.1.3, and we will come back and watch some more of this video. Despite the name, MySQL is a database system, not the SQL programming language.

Read this chapter. Take notes and be able to provide details about SQL, data definition language (DDL), data manipulation language (DML), and Structured English Query Language (SEQUEL). 

SQL is a universal and standard language that interfaces with relational databases. SQL is used to communicate, analyze, and provide results from the data fields stored in a relational database. This next section will cover user-defined SQL objects, also known as functions. Your ability to understand and specify functions reduces the chance of errors in your SQL programming code. Also, remember when we discussed SQL injection attacks while looking at database security? Poorly constructed SQL code is what makes these kinds of attacks possible.

Watch this video on SQL functions and how they are used in queries. Pay attention to the most commonly used functions in SQL. Take notes and learn the purpose of these common functions.

Read this chapter and take notes on the purpose and use of the clause SELECT and how the INSERT and DELETE statements are used to make changes to data. Also, note how functions are used in these statements.

Watch this video on aggregate functions and views in SQL. Pay attention to the summary of the SQL Queries slide. Take notes on the definition and explanation of summary commands for information. For example, COUNT, SUM, MAX, MIN, and AVG. How does understanding SQL programming language help you manage millions of rows of data?

Read this article on MySQL features you need to know. Pay attention and list the reasons that explain why MySQL is important. How does MySQL provide high performance and data security? 

Now, go back to the tutorial you watched in Unit 5.1 on SQL. Watch this video from 1:54:00 to 2:41:00. Follow along with the tutorial, which explains MySQL functions and queries. 

Watch this tutorial from 2:41:00 to the end.

This unit described SQL and provided a summary of basic operators. SQL is a universal language that is used to manage and access an RDBMS. SQL can have user-defined and system-defined functions. SQL allows users to ask questions or conduct inquiries on data. This is done through the use of RDBMS software for SQL.

MySQL is the RDBMS software learned in this unit. This is an open-source database system that is in wide use. Using the SQL language to communicate with a query in a database system is one way to reveal results. SQL can be used to reveal group results and Boolean values based on clauses and operators. Next, you will learn how to request organizational data from RDBMS operating on the internet.

Read this article, paying attention to the various methods to collect data from the internet.

Watch this video on how APIs are used to gather information from a wide variety of web sources. Consider how APIs can also be used to help e-Business and e-Commerce gather data from a wide variety of web sources. Then answer this question. How are APIs used to collect and store consumer data? What are some of the ethical issues associated with this collection and storage of consumer data?

Now, watch this tutorial on the Python Web Scraper. You do not have to download Python. Watch the tutorial and follow along with the presenter. Pay attention to how Python API was used to request online user information, cookies, and JavaScript Object Notation (JSON).

Read this article, paying attention to the data abstraction section. What did you learn about the power design methodology called data abstraction?

Read this article. Be sure you can explain the methods (approach) for extracting data based on usability.

Read this article, paying attention to each application used in data abstraction. Be able to explain the purpose of each application and summarize holistic configuration. 

Watch this video on web crawling. Pay attention to the different components of web crawlers' policy, security, identifier, and general purpose.

Read this article and pay attention to the Evidence Act of 2019 and the OPEN Government Act of 2019. Compare these acts with the Health Insurance Portability and Accountability Act (HIPAA), Personally Identifiable Information (PII), Family Education Rights and Privacy Act (FERPA), and the National Institute of Health (NIH). What happens when restrictions are applied to data that is already available to the public?

Watch this video on the archiving and sharing of scientific data. Pay attention and take notes on the definition, meaning, and explanation of data sharing as well as how one should plan for data sharing. Then think about other contexts in which data archiving and sharing might be appropriate. What are some of the general considerations relating to data archiving and sharing? How can these general principles be applied to a specific situation?

Now, watch this video on the benefits of data sharing. Pay attention to discussions on the purpose of data sharing and the benefits gained from sharing data between users and agencies.

Distributing data improves our ability to learn more about a topic. Organizations distribute data by publishing it using different platforms. This is also known as discoverability. Publishing makes it easier to share and locate data from other researchers and industries. However, it is important to discuss the pros and cons associated with sharing data prior to distributing it through publishing.

Read this article and pay attention to the purpose of why the internet was built. What distinctions can be made about the advantages and disadvantages of data sharing?

Watch this video on how data sharing can improve patient safety. How can data sharing improve the healthcare industry?

Local and international issues and barriers are associated with data sharing. Institutions and publishers revisit publishing requirements on a continual basis to address these concerns. Therefore, revisiting publishing requirements is considered a continuous process improvement strategy to incorporate agreements on data sharing between organizations.

Read this article and take notes on the ethical concerns and suggestions listed in each case study. What actions can you recommend to an employer to mitigate obstacles and issues associated with data sharing?

Watch this video and think back to the project lifecycle process. How well does the project lifecycle process address the criteria for data-driven decisions?

Read this article on being data-driven. Under the Project Lifecycle section, read the four sections: (1) Analyze and Plan, (2) Design and Develop, (3) Deploy and Implement and (4) Cross-Cutting: M&E.

Read this article and pay attention to how companies achieve high-quality performance for value creation. Focus on the selection of KPIs and the discussion. How can organizations improve sustainability in their strategies to improve certain KPIs?

Read this lesson on data warehousing and data mining. Pay attention to the difference between data warehousing and data mining. Answer the practice question at the end of the lesson.

Watch this video on data warehousing architecture. Which schemas can be applied to one or more of the industry services listed in the previous article?

Read this article and pay attention to the data mining techniques, classifier development, and evaluation criteria. Then take notes and understand the difference between supervised and unsupervised learning models. Finally, read the summary and discussion section of this article. What distinctions can be made about the three major purposes of problem-solving items using data-mining techniques?

There are different types of data warehouses, and each has a specific purpose within an organization. Remember, it is important to use the correct type of warehouse to support the "decision support" model being employed. Decision support techniques such as classification, prediction, time-series analysis, association, clustering, and so on will each have their own unique data needs. Correctly designing the data warehouse will ensure the best possible evidence to support strategic and daily decisions.

Managing data is an important function in the administrative process. Because organizations use data to guide decisions, decision-makers rely on you to produce a data management plan for sustainability, growth, and strategy. As you start to interact with decision-makers and the decision-support systems they use, you will also find that additional study of the models employed through a course on quantitative methods or decision-support technology will prove useful.