Data science and Data analysis are somewhat different methods, due to the use of different elements and tools. Analytics, on the other hand, can be considered as the systematic computational analysis of data or statistics.
Data science is a rapidly growing field in today’s world with increasing diversity in its use. Data scientists nowadays find more and more innovative ways to implement big data solutions in our everyday life.
It can be understood as collecting existing data in addition to the creation of new data which can then be used to derive useful conclusions and helpful insight from this exercise. A use case in terms of using data science for analytics can be understood as to how a data scientist will use data science to accomplish their goal and draw useful information from it.
Use cases in data science are made up of three main elements: an actor, a system, and a goal. Here is the list of top 10 data science uses in analytics being used lately:
1. Voice Recognition
Speech recognition has come a long way in a comparatively short duration of time. These days, you can use this feature on widely common devices like smartphones and laptops, making it more affordable for everyone. This system works on the principles of collecting data, processing it, and giving you a useful output as a product. The most common example can be from the times when your kid is stuck at doing his/her assignment and asks Alexa or Siri to look it up without bothering to do a physical search. In this example, the topic of search serves as input and the results for the same are considered as output.
2. Image-based Recognition
It is an interesting feature available nowadays on all kinds of websites including prominent search engines like Google. Through this feature, it becomes so much easier to search for anything you’ve got an image for but are unable to remember its name or the times you’re looking for a similar item online that you saw earlier. Although it’s still evolving and probably has a long way to go before reaching the accuracy levels of voice recognition, it still gives us pretty decent results in its current state of development as well. It is also useful for social media networking sites like Facebook and others to tag your friends better with the same principle by analyzing your already available data.
3. Internet Searches
All search engines are becoming faster and accurate at giving you what you’re searching for in the shortest amount of time possible. One of the key concepts which help these engines to achieve this goal is by using data science algorithms to process larger amounts of relevant data as input, in a shorter time to provide you with the best outcomes. It also uses data from your previous searches to make it more relatable. That is probably why your search results might differ from someone else even if when you’re searching with the same keywords, based on the algorithm’s approach towards your searches.
4. Targeted Marketing
Many people have noticed this pattern of recurring recommendations or advertisements for some product that they searched for online. This is a sound example in the field of marketing by data science use to increase customer growth by companies. MNCs and other corporate giants are some of the biggest data science application consumers because they acknowledge the fact that many of their potential clients are on the internet several times a day and then use this information to refine their marketing strategy.
5. Predictive Systems
YouTube is another solid example of using data science case analysis to better determine what people are looking for by studying their previous watch history and searches. Similarly, Netflix can also use your past watching history to construct a better algorithm to analyze and predict what you may be interested in watching next. Other than sites providing visual entertainment, sites like Amazon or Flipkart can also provide you better suggestions for recommended items based on your past searches and data collected from other similar individuals.
6. Online Dating
It might seem uncanny when sometimes dating websites come up with such accurate matches for you from time to time, but before you get spooked let me tell you the science behind it. So basically what these sites do is by asking you to fill in your choices, hobbies, and preferences. Then, it forms a pool of data which then can be used as input for their data science algorithms which process and a large amount of data and plays cupid by finding you just the right matches as a result.
7. Cost Comparison Websites
As a lot of commodities can be bought and booked online nowadays, there is a growing number of sites that offer similar options for the same, which makes it harder to know the best price available for the same product on all the platforms. Thanks to price comparison websites, which use data science algorithms to make the comparisons for us and present us the results as output price comparison has never been easier.
8. Product Delivery
Other than creating a lot of job opportunities, e-commerce is also playing an important part in making businesses like product packaging and delivery grow as well. With the increase in the size of the market and ever-increasing demand, the delivery services have also taken a leap in its efficiency with the help of data science technology which makes it easier to predict the best routes for delivery services to take for a more sophisticated yet simple to follow the approach for reaching their destinations with the minimum investment.
9. Healthcare
There are a lot of applications for data science in healthcare, ranging from tumor and anomaly detection, drug development to simple yet vital medical practices such as making a diagnosis. AI-powered virtual assistants have played a major role in making this sophisticated task which requires a personal assessment of a lot of data by a medical professional to come to a decision much easier and faster. Due to such facilities, it has also become easier for the patients to skip going to hospitals for minor ailments and yet get a near-perfect diagnosis and treatment recommendations for it from the comfort of their homes.
10. Fraud and Risk Detection
Other than having direct online uses for data science algorithms, it has gained increasing importance in the finance sector as well. For example, in the past, it required a lot of manual labor on part of financial institutions like banks, etc. to go through a large sum of data and determine suitable candidates in need of financial support like loans. But nowadays, with data science algorithms, it has become manifold easier as AI algorithms can analyze the applicant’s past expenditure behavior and loan fulfillment to determine how risky it would be to grant them a loan. All this can be accomplished, in a shorter time than it was before, which is why these days, loan approval can take a few minutes compared to weeks in the past.
Summary
With advancements in science and technology, data science is not just limited to being used online. It is finding more and more applications in other physical sectors to help decrease the need for manual labor with better or similar results compared to the past. We can only wait to see what data science has in store to offer our future generations.