The combination of algorithm development, data interference and technology used for solving complex analytical problems is known as data science. At the core of all of this is raw data, loads of information being collected and stored in warehouses for data. There can be a lot learned from this data through a process called data mining. With the help of all this advanced data, capabilities of machines are advanced. At the end of the day, data science is all about using the available information in the most creative possible ways to help generate business value.
Finding data insights
Data insight is an aspect of data science that deals with uncovering patterns in data to help generate business value. This is done by searching and filtering through data at the lowest of levels to figure out complicated behaviors, interferences and trends. Hidden insights that are obtained can help a business make smarter decisions. A few examples of how data insights are being used are:
- To understand and adapt to future demand, proctor & gamble use time series models which are made with the help of a lot of research from the data they have regarding the trends the company has seen.
- Netflix is known to create user specific content. This is done by the help of the data collected on a user’s behavior and watching pattern. It helps them select out similar movies that the user might possibly love to watch.
- Target, a supermarket chain uses data to monitor their customer’s behavior towards products and how they react. With the help of this, they modify it accordingly to gain maximum sales.
So, how do these data scientists get these insights? The whole process starts with data exploring. Data scientists tend to turn into detectives when posed with a question that challenges them. They try to investigate leads by attempting to understand characteristics and patterns present in the data. A huge amount of analytical creativity is required in order to perform such a task.
Data scientists may then use quantitative techniques to go deeper into the data if they feel necessary. They use techniques such as segmentation analysis, inferential models, synthetic control experiments and time series forecasting to name a few. A data scientist intends to bring together the data into a more presentable and understandable manner. Data driven insight, hence, becomes very important in providing guidance in a strategic manner. In this process, a data scientist acts as a guide and a consultant to business stakeholders as to how they are supposed to go by the findings they have received.
Expertise in mathematics
Data insight mining and building data product at the heart is based on being able to view data in a quantitative manner. The dimensions, textures and correlations within the data which are expressed mathematically. To find the solutions to using this available data acts as a puzzle of quantitative technique and heuristics.
So, if you have wanted to be a part of this wonderful profession that is changing the way we operate, you can undergo data science training.
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