5 Ways Data Science Can Help You Work Smarter, Not Harder!

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5 Ways Data Science Can Help You Work Smarter, Not Harder!

The world of decisions today runs on data. From every time we do a Google search, or use our smartphones to each of our everyday activities, we leave a trail of data on our choices, lifestyles, and habits.  The internet and total volumes of our data are being efficiently managed by the ever-adaptive data science training applications of AI, ML and Deep Learning. Data is the basis of enhancing our lifestyles and entertainment, enabling our banking and communications and empowering our financial productivity and economic growth.

What is data science?

Data science uses the large volumes of data we produce to make logical conclusions, develop models and generate forecasts and predictions through an intricate process of cleaning raw data, parsing and processing it to finally using algorithms to resolve issues and problems. Businesses thrive by using these in-depth insights from Data science training to make decisions related to their productivity, efficiency, growth, and management. It is no wonder then that many of them are heavily invested in the benefits of data science.

The five-pronged strategies for businesses:

Here are five ways in which data sciences make your operations smarter, less expensive and more efficient.

Sentiment analysis:

Sentiment analysis is fast becoming essential before taking decisions on branding, product launches, marketing areas, and even posting information on social media like Facebook, Instagram, and Twitter. Social perception analysis is easily achieved by data science that wades through very huge volumes of relevant data to provide you specific sentiment analysis to base your decisions upon. Advanced techniques and tools like RapidMiner can help you not have to rely on gut-feeling instead. With effective sentiment analysis, one can correct their test market efforts without it being an expensive waste of resources, time and efforts.

Relationship value attribution:

ROI is directly related to customer satisfaction. However, all customers, clients, products, and partners are not of equal value. ROI is determined by the resources spent and time and effort spent in acquiring the business.  Hence relationship value attribution becomes crucial in determining the allocations and budgets spent. Using logic and weights data sciences makes a distributional array of your calendar of events in professional relationships, which helps target the right customer at the right time, improve your productivity and the effectiveness of your UX experiences.

Future demand forecasts:

Demand and supply gauging is the crux of business decisions. The entire process of planning, sourcing, resource allocation and budgeting is dependent on these choices. It is improbable that you will treat such an important decision lightly. Data analysis and data science training when done right and on sufficient relevant data can be very accurate in predicting demands, making forecasts, improving your stock and inventory, tweaking the logistics, providing the metrics for efficient performances and enabling all decisions that lie in between. Of particular use in e-commerce platforms and stock market-based products stocking, the price differences and rates are constantly changing and too little or too much can have a tail-spinning effect.

Fault finding analysis:

No organization is perfect and has tremendous scope to discover ways to encash its strengths and counter its weaknesses. The larger the growth of an enterprise the more difficult it is to spot weaknesses much less rectify them. Data analysis can fill this gap and provide a complete weakness analysis reports to help with rectifying the fault-finding analysis insights. It provides you with the overall view and how each of the departments dovetail together to spot the weaknesses early on.

There have been many instances of these inter-relationships not being corrected in time resulting in over-production, product starved markets, errors in logistics leading to rejections and losses and so on. Underperformance is quickly spotted by data science techniques and applications.

Gauging trends:

Data science can monitor large volumes of data effectively to spot even distant emerging trends.  Since the process goes on continuously and behind the scenes due to automation and AI the algorithms can find and highlight them with little or no manual investigation. Trend analysis is one of the biggest benefits that can help you revise business strategy and models while staying ahead of the curve of competitors.


All businesses can benefit from data science used effectively. It is the platform on which you can base your new products, build brands, strengthen the lacunae, and make effective allocations of finance and resources. The timely decision of data science training is enabled by putting forecasts and predictions which are data-based in the hands of decision-makers. If you are interested in learning more about data science do a training course at Imarticus Learning the pioneers in data science education. Why wait?


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