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Data Analysis - Yelp |
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Restaurants have huge potential to impact on the country as they play an important role in business and social life. Both minor and major events are celebrated in the restaurants so they lie at the heart of our lives and thus opening a successful restaurant is dream project for most of the business owners. So, we are here to help in fulfilling the dreamers who want to own their restaurant, and to achieve this, we have taken publically available yelp dataset. Since this dataset is reliable and can be used in any application, we have used JSON files in an innovative way to answer the queries of the business owners. The data has been analysed and visualised using python and Tableau.
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When a person plans to start a business, he/she will be bombarded with queries for which finding the accurate answers make all the difference in the business. There is so much of data on the internet which need to be discovered, pulled, cleansed, analysed, filtered, transformed and finally converted to retrieve the required information. Based on this information, one has to plan the business keenly but for a common man, it is a tedious task as it’s difficult to keep himself/herself updated on the current technologies all the time. So, we have come up with the scalable dashboard using which any user can interact to fetch substantial info required to start a successful restro across various parts of the United States.
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The developed dashboard is interactive and users can discover the information that has been hidden in the form of layers through effortless interactions. The main dashboard helps to draw a great quality of information in few milliseconds about the relative ratings in the prominent states (NV, AZ, PA, NC, IL, NY) of the United States. It will aid to grasp the order of ratings in a state which has been represented in different shades of effective purple color i.e. dark color represents the total number of corresponding rating is pretty high. For example, North Carolina has the darkest shade for rating 4 indicating there are more number of 4 ratings comparatively. Based on this info, user can strategize the business plans. For example, if a state has the highest number of rating two then he should discover all the cons of the restaurants present in that particular state and should emerge with a well facilitated restro to attain the popularity.
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In the second phase, one could see the number of reviews received for various categories (Japanese, Sushi bars, coffee & Tea ... ) for a chosen rating with a click of a button. This assists viewer to comprehend the contribution of each category towards the total average rating. If certain set of categories have less review counts for high rating then more particulars/statistics need to be collected for those classifications as opening a cafeteria(or a business) in one of those categories will have a high probability of success. On the similar note, if any category has received pretty high review counts for high rating then likelihood of favorable outcome gets reduced as visualization evidently reveals that the existing restros are already meeting the customers expectation. This is just one perspective which is being explained and justified here but our efficacious visualization has competence to expose numerous concealed patterns.
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Now let's talk about the most chaotic subject which is the features which need to be incorporated to drive more customers along with serving delicious and nutritious food. There are innumerable attributes to pick from, but cautious and economical decision along with the innovative features help to get recognized among other recurrent restros. To make spectators piece of work easier, we have designed enthralling visualization which reflects the features available in low and high rating restros with a quantity indicating the number of restaurants having the corresponding features. Suppose if wifi has the highest number followed by facility to drive through then employer can include both or if there is any economical constraints then based on further inspection and interaction with the panel, he can derive a conclusion and execute it.