‘Data science’ is not a scary phrase, it’s imperitive for businesses to stay competitive
“Those who own data own the future, but only if you know what data you’ve got,” said Steve Holyer said during his presentation at Big Data LDN. And he’s right. In 2019, data is being created, stored and shared at an alarming rate, but data is useless unless you can collate it, analyze it and learn from it, which is where data science comes in.
What is data science?
If you see dark clouds, you can probably predict a storm. This is because your brain sees and feels this information, and from your past experience you know it means a storm. You probably move inside, because your prediction led you to a logical solution. Scale the clouds up to include data from almost everything – smart phone locations, CCTV footage, grocery store purchases and online searches. Brains get overwhelmed with this much data, but technology doesn’t.
Data science is a combination of tools, algorithms and machine learning that finds patterns from data. It will use known information and historical evidence combined with machine learning algorithms to make future predictions. Data analytics and data science give context and help form patterns – in the information age, this is cruical.
Why is it important?
Firstly, like getting out of the rain, data science can make predictions, which can be adressed and resolved with logical conclusions. Secondly, when data is being collected and collated, anything that stands out is noticed. This means that posibilities of risk and fraud are seen in minutes, not days or months. Thirdly, organizations can see, at a glance, who’s buying what, where and when. By understanding the target audience, any company can improve its customers’ experiences.
Introducing it into business
In the information age, data scientists play important roles in businesses, but not every company has the capacity for them. This is why companies like data.world were created. This Texas software startup creates a searchable, cloud-based catalog of a business’ data. It then uses specific graphing technology to help visually explain and map that data. Think of Facebook’s newsfeed and profiles mixed with Google’s searchability and library of information. data.world’s catalog is an inventory of metadata. The company uses it to classify and filter data, which is then better rediscovered, shared, understood and used.
Are you developing a new data science tool? Did you know your work could be eligible for the R&D Tax Credit and you can receive up to 14% back on your expenses? To find out more, please contact a Swanson Reed R&D Specialist today or check out our free online eligibility test.
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