What is data science?
Business intelligence (BI) captures business data like transactions, as well as relationships between entities like people, companies, locations etc. Data is consolidated from multiple sources, it is cleaned and loaded, and business logic and rules are provided by the end users. Following this, actionable insights are outputted.
However, data science does not require any business rules to be applied before analysis takes place. Depending on the data source and type, a data scientist might employ a specific combination of statistical methods, big data tools and data mining techniques to a data set to gain insights. While a BI analyst will provide analyses that have been asked for by the business, a data scientist will often provide alternative insights and convey the value of that analysis to the business.
- Data science gives you a quantitative understanding of how your business relates to the world around it.
- Data science helps you to ask the right questions of your data in order to maximise its value to your business.
- Data science takes advantage of tools that sit outside the traditional BI stack.
Where's the value in data science?
Because data science is heavily statistics focused and uses tools outside of the typical BI stack, you can begin to analyse data in new and innovative ways and glean insights from data that you would not have gleaned otherwise.
Business intelligence focuses on delivering the answers to questions that the business knows to ask. In a nutshell, the role of a data scientist is to maximise the value of your data. Unlike in business intelligence, data science seeks to reveals patterns and relationships in your data that you may not have anticipated, and presents new opportunities that do not arise from a typical BI solution.
This is where data science comes in
The Consolidata Data Platform can build powerful predictive models with big data, scrape external data, enrich your current data sources with new and interesting open source data, and perform cluster analysis on data like you would with customer segmentation.
- Do house prices affect demand for your product? By scraping house price data and other similar data, you can study correlations between product demand and external factors.
- Do changes in your revenue correlate with changes in the weather? Find trends or seasonal changes in sales for your products.
- Why do certain customers behave in specific ways? What is the cause of certain patterns of consumer behaviour?
Engaging in data science
Asking these sorts of questions is the cornerstone of data science, and the answers are often surprising. Data science often fits into a wider data analytics solution, and utilises our full range of technology, from SQL Server to machine learning with Microsoft Azure.
Engaging in data science with Consolidata is your first step towards an enriched understanding of your business and its relation to the world around it.
Discuss your data science challenges. Engage Consolidata