Big Data

The more we can analyze the data, the more successful we will be

Big Data

The more we can analyze the data, the more successful we will be

Big Data


Data Science is an evolved form of statistical science that can be used to create value from a large body of unstructured data. for example, provide answers to many questions in the field of business; help to make decisions and improve organizational management practices. The massive data that Data Science deals with is known as big data, which includes a wide range of data, including a variety of databases, sales information in an organization, and information available in Social networks and so on. Big data is used by organizations to improve efficiency, identify untapped markets, competitive analysis, and so on. Using classical big data analysis, a large set of information (also known as data mining) is provided; But Data Science uses machine learning algorithms to design and develop statistical models to generate knowledge from the mass of big data. Some confuse Data Science with machine learning; While machine learning is a component of Data Science.
Overall, working with big data is difficult, but it can bring many benefits to organizations. Imagine being an organization that implements a better pattern of customer engagement by examining customer behavior data over the years. Or suppose another organization that can analyze the big data in social networks and measure the attitude and view of customers towards themselves and realize its strengths and weaknesses. In general, big data is a valuable resource in any organization, but it is less used. nexlooks Agency has been studying and modeling in this field for many years and has been able to develop the latest techniques for working with big data in Iran.

• Analyze market opportunities and attractiveness
• Analysis of growth opportunities
• Analyze the effectiveness of advertising and optimize advertising campaigns
• Analysis of the behavior of sales intermediaries, retailers, wholesalers, etc.
• Product analysis (strengths and weaknesses of current products)
• Concept analysis (whether concepts or new product ideas or startup ideas or advertising ideas)

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