Is Data Science the Right Path For Your Company?
Do you feel pressure to hire a data scientist or build a data science team?
Does it seem like others in your industry are reaping the benefits of data science while you’re still struggling to automate your reporting?
Are you being left behind?
Let’s take a closer look.
So What is Data Science?
The short answer: a relatively new field that is often poorly defined and misunderstood. It typically refers to work involving AI/machine learning, statistics, probability, and/or some level of software engineering.
What Does a Data Scientist do?
A Data Scientist tries to answer difficult questions and predict future trends using advanced analytics and complex modeling techniques including (the much hyped) machine learning. They analyze large volumes of data and (sometimes) real time data, which requires knowledge of specialized tools and platforms. Data cleaning, an underestimated and underappreciated part of the process, is vital to success.
What Does Data Science Look Like?
Classic data science problems include: fraud detection in insurance and banking; natural language processing (text analysis) in media and publishing; healthcare analytics for patient outcomes; and consumer analytics for customer acquisition and retention.
What Data Science is NOT: a fast way to get answers to your business problems.
Data science is an adventure: an expedition, not a day hike.
It’s an R&D function and a long term investment. It requires dedicated, and often expensive, resources. Timelines may be long and outcomes can be uncertain.
Are you Ready for Data Science?
What is the state of your data right now?
Is your data organized and defined? Is your reporting in order? If not, you may be better off improving these areas first.
Do you have a defined problem and does it require a data science solution?
Do you have complicated problems that require complex models to solve and/or large amounts of data (think millions or billions of records) or high velocity data (think stock trading)? Beware of data science for the sake of data science or data science in search of a problem. Be sure that you know what your business problem is and that it requires a data science solution.
Finally, can you dedicate the resources needed, wait for a solution, and keep an open mind about results?
If the answer to any of these questions is “no”, you might not be ready for data science - yet.
So What if you’re not Yet ready for data science?
Consider some other ways to get the data insights that you need.
Do you need quick answers to key business questions? An experienced data analyst can help with this.
Do you need to automate or improve your reporting process? Consider a business intelligence or reporting specialist.
Do you have difficulty extracting or connecting data from multiple sources, or capturing data that isn’t currently in a system? A data engineer may be able to help.
Is your problem more of a software problem than a data problem? Look for a software engineer.
A data scientist is not a one-stop-shopping solution to all data problems. Different data professionals, including data scientists, have unique and specialized expertise. You may need a few different types of data professionals to fully address your data challenges.
Where will data science Take you?
Data Science can do a lot for your company once it is ready and has a true need for data science and when you set realistic expectations.
If you’re not ready then data science won’t take you where you need to go and there are more effective ways to get what you need.
About the photos: Shenandoah National Park, Virginia
Thoughts: The Old Rag Mountain hike is probably the most famous hike in the Shenandoah. It’s a challenging rock scramble so if you’re looking for a bit of challenge this is a great hike. If it sounds too challenging there are lots of less ambitious hikes in the Shenandoah or if you prefer to view nature from your car check out Skyline Drive.
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