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Running Head: BIG DATA 2
BIG DATA 2
Big Data
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Big Data
1. Big Data meaning, importance and where it comes from.
It is a term that defines the large volume of data, both unstructured and structured, that inundates a business daily. (Violino, 2019) But it is not the amount of data that is critical. Big data can be analyzed for insights that leads to strategic management moves and better decisions. Big data assists the company in creating new opportunities in growth and absolutely new categories of organizations that can incorporate and analyze industry data. These organizations have enough information on the suppliers and buyers, consumer preferences, and products and services captured and analyzed. The data that comprise big data stores can come from various sources, including social media, scientific experiments, web sites, and other devices.
2. The future of Big Data and if it will lose its popularity
Big Data can develop gradually at an expeditious rate. The "Big Data" buzzword may alter to something else, though the tendency toward increased abilities of computing, techniques of analytics, and management of data of a high volume of diverse information will carry on.
3. Meaning of Big Data analytics and how it differ from regular analytics.
Big Data analytics is the analytics that is applied to architectures of Big Data. This is a new model; to maintain the computational requirements of Big Data, some innovative and new analytics computational platforms and methods have been developed. Big Data analytics differ from other usual analytics, which incline to pay attention on technologies of relational database.
4. The critical success factors of Big Data analytics
They are; a) A precise business goal. Business investment has to be created for the business good, but not for the sake of only advancements in technology. b) Committed and strong sponsorship. c) Alignment between IT and business strategy. Analytics should play the role that is enabling in executing the business strategy successfully. d) A decision-making culture that is based on fact. In a culture of decision making that is fact-based, the numbers instead of intuition, gut feeling, or assumption drive decision making. e) A strong data infrastructure. Success needs marrying the new with the old for a complete infrastructure that works interactively.
5. Summarize the findings of Big Data in sports.
Using the TUN site, I found one article known as data ball describing how data analytics assists in enhancing players of basketball. The Data analytics that is used in this case are expected progression value (EPV). It is used to predict what will happen next depending on the situations of the game; it uses stats like past strategies, players, and formations. Obtaining all of this new data does not mean that basketball will completely change until they totally have insights on using the new data. At the moment, it will give more intuition into the flaws of players and strategies. Like in basketball, sports analytics is enhancing football games. The NFL utilizes all these new facts to understand exactly all the involved data in a play. Like the distance a player runs, the speed of the football in the air, and the speed the players run at.
The NFL does not only concentrate on enhancing the players but on assisting those who are watching to have a better insight into what is going on in each game. The NFL is committing to gaining more data. They use a production truck out of each game in collecting the data and creating stats so that the broadcaster can use to put emphasis on the level of play. This ends up being a lot of data of every player, so most of the sports utilize it to make decisions on when to substitute people and who is better for each situation. For every sport, data analytics is enhancing the game by giving audience members hard stats or improving players. All the used application is for doing sports to be more significant (Teradata, 2020).
References
Teradata. (, 2020). Data Analytics Online Resources | Teradata University for Academics. https://academics.teradata.com/
Violino, B. (2019, October 18). What is big data analytics? Fast answers from diverse data sets. InfoWorld. https://www.infoworld.com/article/3220044/what-is-big-data-analytics-fast-answers-from-diverse-data-sets.html