Driving Business Value with Data Science
Data science refers to the practice of generating insights from structured and unstructured data using methods such as data analysis and machine learning. The business value or commercial advantage of data science depends on the organization which utilizes the concept. For example, a business can use data science to build tools and predict hardware failures. In another instance, Data Science can be utilized by businesses to predict what product/service to release at a particular point of time or even estimate this particular product’s/service’ popularity or how popular a product will be based on its attributes.
Data Science is capable to provide accurate solutions to business problems when and where required. A business can learn about customers’ needs, interests, ways of living, as well as general attitude towards life. The objective of data science is to build bases for extracting business-focused insights from data. For this, the flow of value and information in a business needs to be understood accurately. This understanding can be used to identify business opportunities. For example, inputs about the population of a region along with characteristics such as distribution of age, gender and levels of income can be analyzed. Insights from this analysis can be used to devise accurate business strategies or conceive the idea of a product/service.
Yet, it should be considered that Data Science is a concept. Data Science is not a tool and not even a business strategy with fixed guidelines. The process involves the contribution of a data scientist who will analyze insights generated from analytics and provide recommendations to businesses.
Advantages of Utilizing Data Science
By hiring the services of a professional data scientist company, a business can,
Mitigate risk and fraud: Data scientists will identify data unique sets of data, following which they will create statistical, network, path, and big data methodologies for predictive fraud propensity models. These methodologies can be used to create alerts that help ensure timely responses when unusual data is recognized.
Deliver relevant products: One of the primary benefits of Data science is that it can enable an organization to determine the location, time and audience which will give welcome its products/services. One of the advantages of data science is that organizations can find when and where their products sell best. This can help deliver the right products at the right time—and can help companies develop new products to meet their customers’ needs.
Personalized customer experiences: Inputs from Data Science campaigns enable sales and marketing teams to understand every aspect of the target audience. It will give a good comprehension of a customer’s past preferences, reasons for change in attitude and how much does latest happenings affect a customer’s shopping mannerism. With this knowledge, an organization can create the best possible customer experiences.
How it Works
The first step is to collect all forms of data from various sources on the internet. Data can be structured or unstructured. Structured data refers to information available in a relational database such as employee registers and spreadsheets. This type of data is much easier for big data programs to digest, but only accounts for a small percentage of today’s data. The remaining portion of unstructured data is found in the form of text messages, social media posts, videos, audio recordings, and more.
These massive amounts of data are stored in cloud storage platforms such as Microsoft Azure or Amazon Web Services. Data is then processed and cleansed. Interesting and useful pieces of information are analyzed. A Data Scientist visualizes the possible outcomes of a business for a particular period of time. The strengths and weaknesses of a marketing strategy are displayed through reports as well as graphs. Finally, the Data Scientist provides recommendations which can be implemented through definite business decisions.
Tools and Technologies
Data Science involves the use of programming languages such as Python, R and SQL. An experienced data scientist company should have expertise in these languages as well as tools such as Apache Hadoop and Apache Hive. SGS Technologie features a team exclusively for big data analytics and data science. Get to us for a quick discussion on how we can implement data science solutions as well as strategies for your business.