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Data Science Blog: Instacart Market Basket Analysis

The Importance and Significance of Data Science in Business

The selected blog focuses on market analysis and predictive analysis based on data science techniques and also reviews the significance of data scientists in businesses. This blog was written in order to understand the importance of data science in business and analysis of market trends (Medium, 2017). The major purpose of the blog is to review the concept behind data science and identify the business problems that can be addressed and resolved through data science techniques. In this generation, the uses of technologies and data science programs are growing quickly where it is important to enhance the experience in the field of data science this is a major reason behind the selection of the post so that level of understanding can be improved about predictive analysis, market analysis through data science.

In this modern generation, most of the companies and users are accessing online platforms and internet servers where products and services can be shared easily. The selected blog identified that performing market analysis is a challenging problem for companies where data science plays a significant role and enables the companies to find the market trends and propose significant decisions in the workplace. With the help of data science techniques like linear regression, deep learning, and analytical tools (NumPy, scipy, or Hadoop), business communities can lead market capabilities and review the collected data from the internet significantly.

Predictive analysis is one of the significant features of data science by which the behavior of the customers towards business services and products can be reviewed and identified easily. For example, in the selected blog, the Kaggle team has reviewed that data science can be applied to the retailing companies in order to predict which grocery product will be purchased by the customers so that level of performance and productivity can be improved. Therefore, it is reported that analysis-related problems, predictive issues, and evaluation of customer behavior these are major problems being addressed through data science. In the selected blog, the deep learning technique is used along with the scikit-learn tool in order to perform predictive analysis-related activities in the workplace.

The outcomes of the campaign show that using data science techniques, business communities can find the behavior of customers, perform predictive analysis, increase market capabilities and resolve business problems significantly. The experience has been enhanced and significant knowledge has been gained in the field of data science and its role in the business communities. It is found that the selected data science techniques and tools are significant by which companies can review the collected data from customers and develop significant business plans and decisions so that level of productivity and performance can be improved.

References

Medium, (2017) Instacart Market Basket Analysis. [online]. Available at: https://medium.com/kaggle-blog/instacart-market-basket-analysis-feda2700cded [Accessed 14/3/21].

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