Question

1. Companies create business records of many types and store the electronic files using an electronic records management (ERM) system. Explain why an ERM is a senior management issue and not simply an IT issue?
2. Describe each of the four V’s of data analytics: variety, volume, velocity, and veracity.
3. Identify the primary functions of a database and a data warehouse. Explain why enterprises need both of these data management technologies.

Answer 1

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

Electronic Records Management system consists of the records such as customer records, profit records, transaction details, customer details, vendor details, etc. With ERM system, the senior management people can easily analyze and make decisions. With ERM system, the organizational data can be consolidated and different type of analysis can be done to provide insights. ERM system is a senior management issue because maintaining all the enterprise records cost more to the senior management due to labor cost and maintenance cost.

With ERM system, the records are readily available and easily accessible. This supports faster decision making in an organization which is necessary to address the environmental changes.

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

Variety: The data are of different types and varied from one another. Data are not always the same to represent the single element. Each and every parameter of data is different. An example of customer data in a bank, there will be a variety of data such as customer id, account no, number of transactions, credibility, balance amount maintained, services are chosen, etc. All these data are different and this shows the data variety.

Volume: With data analytics, a huge volume of data can be processed including the historical data. For example, the customer data of the supermarket chain with 120 stores have plenty of customers and this shows a huge volume of data.

Velocity: Data analytics helps in processing the data at faster rate. The information can be achieved from the data quickly in the form of reports, storyboard and dashboard which allows in quicker decision making.

Veracity: Huge volume of data is not always accurate and consistent. The data requires consistent cleaning and accurate data is processed to help make correct decisions.

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

Database

Primary functions of database are to collect, store and organize the data in a specific form which can be easily understandable and accessible. The database also provides information security and retrieve the data by applying certain functions. Mostly database stores data in the form of a table. Database store the recent transactions and provides quick access to the data. This uses Online Transaction Processing (OLTP).

Data warehouse

Data warehouse acts as a repository to store the data and also has backup facilities to back-up the data. The three main functions of the data warehouse are consolidating data, data cleaning, and data integration. Data warehouse processes the historical data and complex queries and it uses Online Analytical processing (OLAP).

Enterprise uses different types of data for a different purpose. Consider a supermarket chain, both the current and historical data are useful for making business-related decisions. A database is used to get the current data and process the customer information as soon as possible. Data warehousing uses historical data and helps in analyzing the customer data of the past to frame marketing strategies, discounts, etc. Data warehousing helps in segregating and cleaning the data. So, only the proper valid data are processed. In this way, both database and data warehousing are important for an enterprise to use the data efficiently.