Currently, there are thousands of data science jobs remaining vacant due to their vast need in real-time. The organizations and companies are employing data science engineers to solve their problems by cultivating their big data sets. In fact, companies who applied data science in their business tend to receive higher ROI than the others. It created a surge in data science jobs which demands skilled professionals in this field.
Coming to India, Hyderabad is becoming a booming tech valley and there are plenty of institutes in who offer data science courses with classroom coaching in Hyderabad. Data science is defined by means of a collection of business tools, algorithms, datasets, and processing that data to problem-solving. It can be applied in various domains like travel, marketing, health, sales, social media, automation, credit & insurance, etc.
The travel industry has been the most benefited from data science since it extracts and processes the data from the traveler’s behavior like bookings, planning, cancellations, etc. Companies tend to invest more in knowing the consumer’s touchpoints and processing the data sets to drive more revenue in return. Most importantly, this industry is lucrative and its competitiveness favors the implementation of data science in travel.
Marketers are the people who should have an exact understanding of their audience for delivering the products or services when people need at the moment. This is called a micro-moment strategy and it has been employed by the marketers with the help of data science.
The healthcare system has plenty of data collected in the form of EMR(an electronic medical record), lab test, clinical diagnostic report, wearables, and survey. The industry is facing struggles in coordinating this data for the usefulness of patients’ treatment. Here comes the data science. It easily helps the healthcare industry to identify the necessary actions regarding treatment and diagnosis.
Whether it’s marketing or sales, you don’t have entire details about your customer database. In this scenario, data science came into effect. It leverages a predictive analysis mechanism to find out the accurate forecast of leads that you can acquire in the future. It tells you that when to approach the customer at what time that the prospect is turning into a customer. Like this, there is a lot more to identify and collect from the sales perspective. Brands are more responsive in creating buyers persona before making any advertising strategy. Data science is the must-win for the sales leaders who can drive more actionable leads to the organization.
Social media plays a major role in users buying cycle and it triggers brands’ online reputation good or bad. Recent days, brands are listening to their audience in a quite logical manner than the traditional way of sales approach. Applying in data science in social media can create impeccable benefits for the organization. Cluster analysis mechanism in data science can able to group the people in different formats and companies can easily speak to their customers using the data they have. Matching a specific audience in the relevant social media platform and targeting the right product is the best thing that can be achieved through data science.
2 thoughts on “How data science has helped businesses to achieve their goals?”
Big data processing now presupposes, as a rule, the introduction of special software systems that allow processing large amounts of data based on the Map-Reduce concept. Hadoop is currently the de facto standard for big data processing. Hadoop is a framework on the basis of which applications for analyzing and visualizing big data are developed. Data storage in this framework is carried out using a special distributed file system HDFS (Hadoop Distributed File System), which underlies Hadoop and allows you to store and provide access to data at once on several cluster nodes. Thus, if one or more cluster nodes fail, the risk of data loss is minimized and the cluster continues to operate normally.
Many companies in the process of their development face the problem of managing increased document flow. There are more and more documents, and it is often not known where exactly they are located-in the field of employees, contractors, or somewhere else. Accordingly, there are problems with the prompt search for documents. The number of persons involved in approving the document increases, and the time spent on approval increases accordingly. In this regard, there is a need for centralized storage of documents, managing work with them in a single information space, and automating the processes in which documents are involved. All these tasks are successfully solved using electronic document management systems