What is Big Data & Data Science?
Data science represents the various processes through which information is extracted from the massive jumble of data collected through various channels. From discovery to compilation, analysis, and modeling, data science can involve a whole host of technologies and disciplines to get results. It incorporates the use of math, computer science, analytics, artificial intelligence, statistics, and more.
Big data is an application of data science that deals with enormous data sets that can be difficult to handle. It makes use of specialized and customized tools and techniques to analyze the large data sets, identify trends, and create predictive models.
Data scientists typically specialize in coding, math, statistics, data analysis, big data tools and machine learning to create predictions and solutions for complex business problems. Degrees in math, statistics, computer science, and engineering provide a solid foundation for a career in data science. Having professional problem-solving skills and knowledge of the subject matter in the targeted field is also beneficial.
Those looking for a more direct career pathway may opt for specialized online programs and boot camps. There are multiple certifications one can pursue to acquire the technical skills needed to become a data scientist. These skills include programming, understanding analytical tools like SAS, Spark, and R, and handling of unstructured data.
Importance of Data Science
When knowledge is extracted from data, it can be leveraged to make key business decisions and develop strategies. The bulk of data is unstructured but data science provides a means by which to analyze it, pinpoint trends, and gain insights that can lead to better solutions.
Businesses have been able to better refine their product decisions thanks to the analysis of the market, product performance, and competition. Through big data analysis, businesses can better meet the needs of their target market. By recognizing trends, businesses can strategize on how to improve customer engagement, better develop their products to meet market expectations, and ultimately boost profitability.
Data science insights are also useful when it comes to the recruitment of talent. Data mining allows businesses to better profile candidates and select those that will fit in best with the existing work culture and have the needed capabilities for the roles.
Digital transformation that stimulates the need for infrastructure modernization makes big data analytics easier and faster. By ensuring the storage of large amounts of data is more cost-effective, secure, and accessible, there is faster processing of data and arrival at the information that will better guide business decisions.
Impact of Data Science In Modern World
Thanks to cloud computing, data science in business is better able to function as the massive amounts of data can now be more easily stored without the business needing to make huge investments in infrastructure. Data scientists can work in the cloud, analyzing all kinds of structured, semi-structured, and unstructured data sets to draw insights. With good access to a variety of free and fee-based tools and programming languages, processing data is made easier and faster. The use of such strategies like binary columnar data storage and sampled data sets can cut processing time and elicit faster results.
Besides helping to strategize and improve existing processes and products for businesses, data science is also great for realizing unseen patterns and inventing radical solutions. It has also proven helpful in handling crisis by identifying the causes of undesirable situations. Whatever short to long term goals a business has, data science can help improve performance.
Career Opportunities
Businesses have long realized that knowledge is power. Data science provides a means by which to harness this power and use it to influence business strategy and decision making. This makes data scientists influential business strategy execution consultants as it is their work that helps make this possible.
The data science field is fast growing and requires a slew of well-trained professionals to take their place in the business world. Being able to analyze data and use this information to solve real-world problems makes data scientists and big data analyst a highly valuable resource. The demand for their services is expected to keep growing over the coming years, with plenty of highly paid job opportunities opening up.
Conclusion
Many organizations especially SME’s needs guidance on identifying the business aspects of data science projects. Most companies are specialized in the market, and their knowledge of strategy execution and implementation of projects is limited. Consultants help identify business processes where data science projects can be implemented.
In addition, the success of the project will depend on if you have the right team working on it. That’s why it’s important to identify the right talent before the project begins to increase your chances of it succeeding.
There are plenty of ways to fill the roles you need, whether it be through LinkedIn job posts or indeed to identify the talent you are looking for full time or part time. Another option is to hire a consultant. They offer expert help for the duration of the project, and also help to train existing staff. One way is to hire a strategy execution consulting firm such as MicroAgility, to provide you with the professional consultants to work with your team. Or if you’d like to quickly find resources and relevant talent, you can explore consulting platforms like iAgility, where they have vetted consultants on demand.
Feel free to explore your options to identify which is the best route for you. Good luck with the execution of your strategy, if there’s anything our team can do to help, let us know!
About the writer:
Sajid Khan is the President at MicroAgility and has over three decades of management and consulting experience. He leads the efforts is many projects including operational improvements, cost reduction, and managing growth while holding key positions in leading companies such as Merrill Lynch, J. P. Morgan, and Deloitte & Touché Consulting Group.
