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Week6DQResponses_BigData.docx

Subject: Big Data Analytics

Q1. Please read the below paragraph and write your opinion. You have any suggestions?

Note: 100 words with intext citation and references please.

A business that may use data to apply predictive analytics to make business operations decisions is a retail store. The types of data that would need to be collected include sales data, customer data, and product data. This information would be gathered through POS systems, customer surveys, and product reviews. The relationships between these data would be identified and used to predict future sales, trends, and customer needs. The same concepts could be applied in a job role to predict future workloads, projects, and deadlines. The retail store can plan ahead what SKUs are most popular and should be stocked heavily. The store can also use customer-provided feedback to see what features are most suggestive of customer satisfaction and acquire products around those features.I work at a medical device startup. We need to purchase key components ahead of time such as screen and LTE modules. Sales prediction would help suggest what are the volume of those components that we may need ahead of time, such that we can be more prepared to stock up in advance.

Q2. Please read the below paragraph and write your opinion. You have any suggestions? Note: 100 words with intext citation and references please.

Predictive analytics is future-oriented, and helps us answer the question “what would possibly happen in the future?” In a big-picture sense, predictive analytics pulls past as well as current data, and turn it into actionable insights. 

One area where predictive analytics have really shined recently is cybersecurity. Nearly all companies nowadays rely on the internet to interact with customers, and thus face the risk of cyberattacks. Internet-tech companies are especially popular targets , since the negative impact can be severe. 

Traditional cybersecurity tactics are effective to a certain extent, but predictive analytics can bring it to the next level by literally forecasting the attacks. If done right, predictive analytical models are like radars that can show the enemy approaching, giving the system valuable time to prepare. These models function by using self-learning algorithms, and detection techniques to evaluate real-time data and network activities. Whenever irregularities are detected in the data traffic flow, the model alerts human security experts, who then can protect against the attack before it happens. 

All in all, predictive analysis can really be a great helping hand when it comes to the domain of cybersecurity. 

Subject: Internship

Q3. Please read the below paragraph and write your opinion.

Note: 100 words with intext citation and references please.

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