Companies create business records of many types and store the electronic files using the electronic record management system (ERM). Explain why an ERM is a senior management issue and not simply an IT issue?

  It is important to know that keeping the business record is not the only thing to worry about with regards to ERM, but there are so many other elements to look at. The role of senior management in the application of an ERM is critical in so many ways. If one may think that implementation of an ERM is an IT-related issue, and then they are getting it wrong because when IT-related side is analyzed, that is a separate thing. For instance, if the senior management is not ready to invest in the latest ERM systems, and they are not able to understand the importance of it, then it is an issue on the side of senior management, not on the side of IT. IT-related issues are operational issues, where an ERM may be having errors, or it does not have the capacity to deal with the latest business processes. Then IT has nothing to do with it, rather they will simply tell the management that current ERM is no more capable to serve the organization, so it is vital for them to implement a new ERM. If senior management does not allow this, rather they insist on using the existing ERM. In this situation, when an organization will face issues in its record-keeping, then senior management should be held accountable because the IT department can’t do anything about it. The senior management should understand that they may lose various competitive advantages if they will not invest in their ERM. If they don’t realize the criticality of the situation, then it will have severe consequences for the organization to face (Henriksen & Andersen, 2008)

2. Describe each of the four V’s of data analytics: variety, volume, velocity, and veracity. 

            Big data analytics has four V’s which should be kept in mind when big data analytics framework is being managed. The first V in this regard is volume. It is one of the main elements of big data because of the huge volume of the data is the actual thing, which constitutes the term of big data. So, enterprises should make sure that they are not dealing with a short amount of data; rather they are having a huge volume of data regarding their business and customers to get better insights. The second V in this analytics is variety. It means that an enterprise should have a variety of data, where both structured and unstructured information is collected and analyzed accordingly. The more variety in big data allows enterprises to have a multifaceted view of things. The third V is called velocity, which means that how quickly the data is being acquired, and at the same time, how data is being processed and analyzed by the enterprises to find the required answers for their business questions. If there is a need to analyze data in its real-time, then it will be considered a velocity challenge for the enterprise to manage. The last V in this analytics is called veracity, which means how authentic data is to be trusted as correct. It is vital for enterprises to ensure that data is accurate and trustworthy; otherwise, the results obtained from the data will be misleading in so many ways. These four V’s are critical to be understood in the context of the big data analytics (MOHANTY, 2015).

3. Identify the primary functions of a database and a data warehouse. Explain why enterprises need both of these data management technologies?

            It is vital to understand that data warehouse and database are both important data management technologies. The primary function of a data warehouse is the collected data from a variety of sources, and this data is collected across the organization, which is later used for analysis and reporting. The best part about a data warehouse is the fact that when data is analyzed, it helps to resolve queries and get insights, which is later used for making better business decisions. It is vital to know that data stored in the data warehouse can be either logical or physical. The other vital function of the data warehouse is to provide a correlation between the existing systems with the data. On the other hand, a database is a data management technology, where information is contained in an organized manner like organizing in tables, rows, and columns. This data is then indexed on a periodic basis so that relevant information can be made more accessible in every possible term. To perform the function of a database, enterprises tend to use a variety of database management systems and software. One important function of a database is to organize and manage online transaction processing. Keeping the primary functions of both data management technologies, it can be said that a modern organization needs both to get as many benefits as possible. The data warehouse can be used to collect data from all corners of the organization, and it is then analyzed to get great insights. On the other hand, when real-time data processing is needed, then a database helps to manage this requirement (Cardon, 2018)