We have jumped from the Information Age to the Age of Insight. Data science has never been more important to the viability of a business. Effective practices can improve revenue, reduce costs, aid in product development, and increase business agility among many other benefits. With the abundance of unstructured & structured data available for analysis, your business should be employing data science teams that can regularly add value to each of your business units.
“Information is the oil of the 21st century, and analytics is the combustion engine.”
– Peter Sondergaard, Senior Vice President at Gartner
How Do Data Science Teams Fit Into Your Organization?
Taking data from an unstructured state through the entire process where it can be utilized by data scientists to develop business value requires a diverse set of skills and roles. From data analysts to data architects and scientists, your data science team needs to understand how to use visualization tools, programming tools, have an aptitude for research and have great communication skills. Not only will these team members need to analyze data, but they will need to be able to regularly present their findings to other business units.
It is not uncommon for data science teams to be siloed with its own floor or area of the physical business location. However, more businesses are turning to a DataOps approach, embedding teams throughout the organization to maintain more pragmatic solutions. The information has shown that isolated teams focus on more sophisticated and expensive solutions, while embedded teams will be able to see smaller, more cost-effective solutions that still move the needle.
Improving legacy systems, developing custom applications or supplementing your development team are just some of the options that you can use to get more efficient and productive.
A Day in the Life of a Data Science Team
In order to extract meaningful, business-focused insights from your data, teams are required to understand how value and information flow within a business and have the ability to see business opportunities in that data. Data science teams are built to consistently find these opportunities to present meaningful upgrades, adjustments and insight for each department as well as the company at large.
The daily life of a data science team is laborious, constantly collecting and cleaning data for analysis. The hunt for true value is wrapped in the scientific method of hypothesizing a business opportunity, then experimenting with data to test that hypothesis. This time-intensive process is key to any business looking for new ideas to stay ahead of the competition.
The initial “discovery” phase is just one aspect of a diverse and complex data science system. The chart below illustrates this system.
Data Science to Application Development
Whether you have a great data science team or not, businesses need to stay ahead of their competition. Improving legacy systems, developing custom applications or supplementing your development teams are just some of the options that you can use to get more efficient and productive.
Next Horizon provides holistic technology solutions for businesses looking to improve sales, increase agility and optimize productivity. From deploying dedicated development teams to building bespoke business applications, Next Horizon uses its 40+ years of experience and award winning talent to solve business problems for its clients.
Categorised in: Application Development