Big data analytics

1.  Excel is probably the most popular spreadsheet software for PCs. Why? What can we do with this package that makes it so attractive for modelling efforts?

Excel spreadsheet is one of the tools that enables one to group data and later use it in meeting all the needs (Bone et al., 2018). Excel spreadsheets can carry most of the tasks as required by the user. One of the reasons most people use them is that they can host an extensive list of activities that one can need. For the users who deal with various data sources and whose decision-making the available data can influence processes, this tool puts them in a better position to arrive at the intended position. According to most of the users, excel spreadsheets have the capability of hosting several do's that enables them to prepare the agendas for the various users, thus making it easy to attain their goals by guiding them through the decision making process. There is almost nothing that most of the users can not have a chance to track using the excel spreadsheet program.

However, although other tools serve a similar purpose and whose features can march those of an excel spreadsheet, it is one of the most influential and less complex tools that users can rely on when they want to solve some of the complex operations that may have an impact on the overall performance of these organizations. Another reason for the popularity noted in the excel spreadsheets among most users is seen in the charts easily used and managed in excel. Further, it can be used in running a descriptive and inferential statistic test that can facilitate business success.

Many researchers and statisticians argue that excel offers a valid capacity that assists users in performing a statistical assessment of databases with many records with commands that can be easily used (Burr et al., 2021). The reason for the high popularity level related to the excel spreadsheet is that the user can define the custom formulas to be used in calculating the reports and financial operations affecting the organization. Another reason for the increased popularity of the excel spreadsheet is that the software enables individuals and professionals with different knowledge to have the ability to keep track of all the sales, the status of the project and invoice reports. To help businesses and the key operations that guide the functionality of these businesses, companies use the excel spreadsheet to have an in-depth assessment of the data to assist in predicting the possible outcome.

One can embrace several approaches to make the excel spreadsheet more attractive in all modelling efforts.  Creating the cell styles to promote consistency is one of the approaches that one can use to make the tool more reliable. Over the past years, the number o companies that need assistance in ways that they should follow to improve their financial stability has increased. The above has resulted in the increased demand for the use of better tools that will propel the companies performance after the right data is used. A reasonable number of companies use this tool to estimate the individual's retirement savings and assess the employees' current salary to predict the future. Most modern-day organizations get to make right estimation to make the right prediction through the gathered data. Further, the use of excel spreadsheets is an essential tool that enables most organizations to review the tax rates and the possible challenges that the organization may encounter when dealing with some of the operations. Users can use this package to understand some of the operations (Laplante & Vernon, 2021).

2. What are the common business problems addressed by Big Data analytics? In the era of Big Data, are we about to witness the end of data warehousing? Why?

Big data analytics refers to advanced analytic techniques to deal with diverse and complex data sets. One of the benefits of using big data analytics is that it enables businesses to focus on local preferences and make appropriate decisions based on the insight created on the data (Hariri, Fredericks & Bowers, 2019). Further, businesses that rely on big data analytics can cut off the costs of operations and therefore ensure that most of the challenges affecting the company are managed. However, despite the complications associated with implementing big data analytics, it is worth noting that there are several business-related problems that the implementation of this tool can assist in addressing. For example, data quality is one of the challenges that most businesses encounter.

 When big data analytics is implemented in any company, it ensures that the company's operations are well designed in a way that can lead to improved functionality. However, the lack of data science professionals makes it challenging for some companies to deal with the data and make the right decision easily. In most instances, these challenges arise when the data to deal with is relatively complex compared to the tools implemented in the organization. Big data analytics is a reliable platform that ensures that companies with and without qualified specialists can use the right technology to easily deal with all types of data and make appropriate decisions that can promote its performance (Gupta et al., 2019).

Data accumulation from different data sources is the other challenge that companies are afraid of in the modern-day community. The challenge linked with this instance is that there are possibilities of minimal chances of the organization, through the managerial team to understand the right area to use a specific data gotten from a given source. For this reason, the use of big data analytics helps solve this challenge since it makes it easy for the data specialists in the company to group the data and deal with the data with much urgency.

Although most companies have started embracing big data, it does not mean that we will experience the end of data warehousing. One of the reasons big data will not bring data warehousing to an end is that the challenges of data warehousing have forced the creation of appropriate measures of handling most of these challenges. Additionally, it is worth noting that data warehousing and big data are not the same, and in that case, they are not interchangeable. Further, in the age of big data, data warehousing techniques are still relevant since they enable most organisations to design most of the unstructured data with the existing data. Therefore, although data warehousing may not coexist with big data, warehousing will form the basis of developing more applicable measures for addressing the possibility of any confusion that may affect the data.

In data analytics, the application of various classes and data sources can determine the magnitude of the possible impact in the respective industry (Gupta et al., 2019). Any organisation's cost and financial spending determine the milestones that the respective data management approach will go. Although big data analytics enables most users to save financial spending, one may argue that the financial spending involved when using the data warehousing techniques is not notably high. Therefore, not many companies will replace data warehousing techniques since, according to them, their budget is not heavily affected by big data analytics. Therefore, we still need a data warehouse. However, the exact solutions linked with data warehousing mainly depends on several factors such as technology stack and internal knowledge. Companies with appropriate technology and specialized teams that allow them to use a data warehouse still see it as a reliable tool for managing all their operations.