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What is the real life examples of Data Science that you use in your job?
I'm an Information Systems Graduate Student looking for professional advice and examples of usage of Data Science in real life, not University project. #networking #business-student
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10 answers
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Corey’s Answer
I cannot think of a single day at job I've had in the past decade where the ability to interpret data hasn't been in demand. Whether it was crunching sales data for trends to exploit, using software defect data to improve operations, or learning how customers use our products to improve UX it's used every day in myriad ways.
As you enter the market, employ your education in any and every possible way at work. This will teach you more than you can imagine; take every opportunity to learn and grow beyond the textbook - especially from your peers. Find an intersection between your other passions and data science to bring joy into your life.
As you enter the market, employ your education in any and every possible way at work. This will teach you more than you can imagine; take every opportunity to learn and grow beyond the textbook - especially from your peers. Find an intersection between your other passions and data science to bring joy into your life.
So inspiring! Thank you!
Denis
Updated
Pavel’s Answer
We use data science and data visualization tools a lot in electronic payments industry to identify major opportunities for financial institutions to improve transaction processing rules and also predict what may be a potential negative impact on future consumer behavior in case those opportunities are not addressed.
Thank you, Pavel!
Denis
Updated
Chris’s Answer
Hi! I use data everyday in my job at Verizon. My team researches issues with usage records falling out of the billing process and look at millions of records that fall out from billions of records each and every day. Without the data science and systems that can handle that large amount of data, we would have a hard time finding the root cause on why some things are going into error. It could be something from a new plan that failed, a specific issue with equipment on the network, or reference data that was wrong or missing that prevented the usage from being properly rated. Some issues are really small, and others can cause millions of records to fail. My biggest accomplishment was finding an error that was causing records totaling $8.5 million in annual revenue to fail into error. Huge win for my team on getting that fixed. It is really rewarding to find issues like that and get them fixed. I use several data systems and there are many more that Verizon is exploring to assist all of us in data management. SQL, Terradata, Hadoop, Tableau, and Cassandra are a few.
Hope my answer helped!
Hope my answer helped!
Thank you, Chris, for a detailed answer. I have never heard of Terradata, I'm going to read about it. For me, it's very important to study what can really be used in real life, and not just legacy tools.
Denis
Updated
Patrice’s Answer
I work for a financial company, so we use data science to model and analyze financial fraud all the time. If you can create an effective algorithm to do this better, financial companies are usually very interested in this.
Yes, fraud detection is what interests me a lot. I'll explore this topic deeper. Thank you!
Denis
Updated
Hemachandra’s Answer
One of the best real life application of data science is modelling COVID-19 virus infection spread among low income and under privileged sections of the population. You can use public data and different statistical methods to identify multiple factors that are negatively impacting the selected population and the impact of mitigation factors in reducing the spreading of infection and the resulting death rate. These models can be applied to countries like USA but to all the countries highly impacted with the virus.
Thank you for an interesting example!
Denis
Updated
Mark’s Answer
One example of how data science is used at a health plan is to target populations. We might have a new care management program with limited resources. Data science can be used to identify the population that would most benefit from the program. We might have a new product that we want to launch, we would use data science to understand which of our current members to target for marketing outreach. We might have a survey we want to take of our customers in regards to customer service and what we need to fix. Data science can tell us which of the customer are the most dissatisfied, so we talk only to those that had a bad experience.
Thank you, Mark! In this respect it's no longer a data scientist's job, it's a marketing manager's job, right?
Denis
Updated
Gloria’s Answer
Hi Denis,
You have gotten a lot of great examples. I would offer one from Learning and Development. I work in a corporate university that has been working on data to compare the job experience of an employee to their current jobs or future jobs in the same job family. So for example, I am an Instructional Designer. I have been an instructional designer in a previous job and have certain skills that are different from someone who was promoted out of a Marketing job. Now say we are both looking to promote into a Sales supervisor job. I want to know the most efficient path to get that job. I could think that I know what I need to learn, but there is an opportunity for a tool to tell you what you need based on your own skills.
This comparison will allow a tool to proactively present a customized training plan for each person. The plan can either be expanding skills in your current job role versus training you may want to take ahead of getting a new job. Between analyzing information (what skills I have or what skills are required for a job), there is also where the data comes from and how its maintained or augmented over time. In addition, the collection of this data may also reveal gaps in the training needed to support the future growth of employees. The data becomes a TO DO list for future training creation within my department. So with one large data collection analysis, we are personalizing the training experience so a person can improve their skills faster and identify future training creation efforts. There are incredible benefits to this work such as employee satisfaction, time savings, and cost savings from doing the work that has to be done rather than the work we think needs to be done.
I think that you are entering an exciting field. I presume that like most fields, you would need to determine your area of focus. I saw that you had mentioned a desire to focus on Fraud, which all companies need. Your challenge there would be to determine if expertise in a specific type of business would add value to your data analytics skills. For example, would you want to work in preventing data breaches of customer information for a company like Target or Chevrolet? I am not sure how much a type of industry changes what you do. I know that for my job, expertise in telecommunications or hospitality does not impact how I do my job that much, although it may impact the solutions that I can apply. For example, my last job had a lot of third-party vendors, so I had to create training that avoided co-employment issues. I work at a company now where video is a preferred method of training, so I had to augment my skills to allow me to create videos.
Gloria
You have gotten a lot of great examples. I would offer one from Learning and Development. I work in a corporate university that has been working on data to compare the job experience of an employee to their current jobs or future jobs in the same job family. So for example, I am an Instructional Designer. I have been an instructional designer in a previous job and have certain skills that are different from someone who was promoted out of a Marketing job. Now say we are both looking to promote into a Sales supervisor job. I want to know the most efficient path to get that job. I could think that I know what I need to learn, but there is an opportunity for a tool to tell you what you need based on your own skills.
This comparison will allow a tool to proactively present a customized training plan for each person. The plan can either be expanding skills in your current job role versus training you may want to take ahead of getting a new job. Between analyzing information (what skills I have or what skills are required for a job), there is also where the data comes from and how its maintained or augmented over time. In addition, the collection of this data may also reveal gaps in the training needed to support the future growth of employees. The data becomes a TO DO list for future training creation within my department. So with one large data collection analysis, we are personalizing the training experience so a person can improve their skills faster and identify future training creation efforts. There are incredible benefits to this work such as employee satisfaction, time savings, and cost savings from doing the work that has to be done rather than the work we think needs to be done.
I think that you are entering an exciting field. I presume that like most fields, you would need to determine your area of focus. I saw that you had mentioned a desire to focus on Fraud, which all companies need. Your challenge there would be to determine if expertise in a specific type of business would add value to your data analytics skills. For example, would you want to work in preventing data breaches of customer information for a company like Target or Chevrolet? I am not sure how much a type of industry changes what you do. I know that for my job, expertise in telecommunications or hospitality does not impact how I do my job that much, although it may impact the solutions that I can apply. For example, my last job had a lot of third-party vendors, so I had to create training that avoided co-employment issues. I work at a company now where video is a preferred method of training, so I had to augment my skills to allow me to create videos.
Gloria
Thank you for your detailed answer, Gloria! There are so much knowledge out there that we need some kind of tool to help us decide what to learn. Great example!
Denis
Updated
Kate’s Answer
Datascience can be used to grow businesses! For instance, the data science team at my company helps us to identify current customers who are likely to buy more from us. They make our job easier, by telling us where to focus our efforts!
Thank you, Kate! That gives meaning to what I have been studying. Thank you!
Denis
Updated
Kelvin’s Answer
In my role as an Incident and Problem Manager, we collect a god amount of data every month. Based on upper management requirements we create reports to meet their needs. This allows us to identify trends to proactively and reactively respond to, it also allows management to make important decisions based on the information that we provide. Data Science is a very critical and important part of any business.
I appreciate your reply. Thank you!
Denis
Updated
Brian’s Answer
I use data science all the time when trying to model customer populations. When testing software, we need our databases to simulate depth and breadth of customer databases, but we can't use actual customer data for privacy and security reasons. Using statistical analysis on a spread of customers reveals patterns in data shape and software usage. We look at those patterns to create our models and build a range of scenarios.
I have never thought about using data science in testing. Thank you for an eye-opening example!
Denis
Glad to help. :)
Brian Weissman