Using Big Data and getting a job in that Market

A lot of businesses are interested in big data. Big data is a term for the total quantity of information gathered by people and organizations as they go about normal activities. Properly analyzing big data can help influence decision making and change organizations for the better. Only focusing on one particular trend in data collected can cause problems.  Problems With Data Analysis Suppose that a car manufacturer sells 1 million cars in a year. It gets all sorts of information about how the vehicles are being used. Customers make complaints about repairs. The government passes certain laws about how new cars should be manufactured. Shareholders want more profit. Employee unions want more wages. Problems with data analysis begin when an organization fixates too long on one type of data. If the management of a company decides that the production of vehicles is the most important variable to focus on, profit will go down. Employee wages will go down so that the manufacturer can afford to produce more cars. There will be more strikes, as employee unions demand a return to higher pay. The same is true for focusing on any other type of information. Good Data Analysis A healthy data analysis strategy determines several big priorities to try to maximize. For a company, that might be profit, employee happiness, and government approval. The other types of information will not be valued as highly in this data analysis strategy. Each of the major priorities has to bend to the will of the other more than they like to. Employee happiness must suffer a little so that profits will be a priority. Government approval must suffer a little so that employee happiness is not terrible. Profits must suffer a little so that government approval is obtained. If an organization has too many priorities, there is a breakdown in performance. Jack of all trades becomes the master of none. If there is a new priority that must be added, another priority might have to be deleted or made smaller.  Interpreting Data There are many ways to interpret data. The method that an organization uses will often determine its success. If only subjective feelings are used to interpret data, the company will buy nice corporate cars because executives feel like doing it. Spark transformations begin when more objective methods like statistical analysis are used to interpret data. Statistical analysis takes data and puts it in number format. If the important priority is profit, this would mean plotting how much profit the organization made over time. Different math terms like the average and standard deviation from normal are then used. This can help people with different opinions on the priority have an objective standard that they all agree with. 5 Useful Jobs In Big Data Analysis Most jobs require some level of data analysis. Deciding how many tomatoes to put on a sandwich at a restaurant requires understanding the company budget for tomatoes and the customer preferences. Some big data jobs are particularly challenging because an organization has to decide how many priorities to have, and how to balance them properly. Some good jobs that are catered to big data analysis include mathematician, engineering, accounting, law and politics, and corporate management. Most big data jobs require some education after high school. Many require a graduate degree.  Conclusion  Big data is a challenging field that most organizations and people need. Sadly, it is not always an easy task. It is particularly hard to practice if only focusing on one priority. It is also hard to practice if there are too many priorities. Too many priorities become no priorities. Finding the proper balance of enough priorities makes a healthy organization.