Big Data for Business (2/2)
In this lesson, you’re expected to learn:
– the importance of Big Data analytics in today’s world
– how different industries use Big Data to their advantage
Importance of Big Data
Big data is not the goal but the means to achieve our goals. Some companies get confused and seem to think that the objective is to implement a Big Data solution. But this is the wrong approach. Big Data is the means to achieve an organization’s targets.
For example, suppose we are already capable of analyzing our customer data, and that our current systems are capable of handling the size and speed generation of this data. Then what is the point of implementing the same solution on Big Data? In that case, there would really be no point. However, the benefit of Big Data relies on the fact that it can help us solve more complex problems, or analyze data that we could not explore with traditional systems.
In summary, Big Data is a medium that enables us to extract more value from data. But the value itself is not in the Big Data technology but on the insights we are able to extract from our data with these tools.
Benefits of Using Big Data
The main advantage of Big Data is that we can take data from any source and analyze it to find answers that enable:
• cost reduction
• time reduction
• new product development and optimized offerings
• smart decision making
Enlarged version: http://bit.ly/2nmM8PS
Moreover, when you combine big data technologies with advanced analytics, you can accomplish business-related tasks such as:
• Determining root causes of failure, issues and defects in near-real time.
• Generating coupons at the point of sale based on the customer’s buying habits.
• Recalculating entire risk portfolios in minutes.
• Detecting fraudulent behavior before it affects your organization.
Big data can increase the performance of organizations across practically every industry.
Next, we will illustrate how different industries can benefit from using Big Data.
Banks have a vast amount of data. Their customers make transactions daily. The stores holding one of their POS terminals register thousands of transactions everyday. Thus, every bank has to deal with data streams from countless sources and they need to transform this data into knowledge. For example, it’s important to understand customers and boost their satisfaction, but it’s equally important to prevent churn, or to sell new products to their existing customers.
Moreover, a bank deals with loads of credit card transactions daily. Hence, detecting in real time, whether a transaction is fraudulent or not is vital to minimize risk and fraud while maintaining regulatory compliance.
Additionally, external data can also enhance the knowledge of a bank about its customers. A bank usually knows a lot about their active customers, but has little information about passive customers who opened an account but do not use it frequently. In this case, external data becomes extremely valuable.
Governments handle lots of data regarding their country. In many cases, this data is not sufficiently exploited. However, government agencies that are able to harness and apply analytics to their big data, can use it to deal with problems such as traffic congestion, crime prevention, and promotion of industries.
Moreover, if this data is processed, analyzed and aggregated, it can also be released as open data so that the population or a local industry can benefit from it. Despite there being many advantages to using big data, governments must also address issues of transparency and privacy.
3) Health Care
Big Data in healthcare can be used to predict epidemics, cure diseases, improve quality of life, and avoid preventable deaths. However, privacy protection becomes even more important in this case.
How can big data aid disease diagnosis?
For example, predictive models can help to detect cancer at a preliminary stage and save lives. Currently, the challenge is to understand as much about a patient as possible, as early in their life as possible. If this is done, one can detect early signs of a serious illness and treat it before it becomes a more serious (and expensive) threat.
In the retail sector, big data and advanced analytics can help companies to better understand their customers and make them personalized offers. This is happening in the following ways:
This is one of the most common use cases of big data and analytics in retail. New products are recommended to customers based on a customer’s purchase history, and the history of others similar to him. Similar to this concept, Spotify or Pandora recommend you the next song you’d be willing to listen to.
https://www.linkedin.com/pulse/top-5-big-data-retail-use-cases-powered-apache-spark-machine-karanIf you’d like to refer to this later, you can find the link in the Additional Material section.
All of us expect stores to anticipate our needs, to have the products we want on-hand, to interact with us quickly and fluently, and to adapt to our needs as they change. When this occurs, our satisfaction increases. Thus customer 360 help retail companies to have a 360-degree view of their customers.
Path to Purchase
Analyzing what drives a customer to purchase a product, or the path to purchase, is another way retail companies are benefiting from big data. Big Data is helping to understand consumer buying patterns and habits.