Why Big Data Is Essential For Analytics?
The tremendous usage of internet all over the world is generating humongous amounts of data every second and basic analytics methods fail to keep pace in collecting, uncovering hidden patterns, establishing correlations and delivering valuable insights. The concept of Big Data has grown significantly in the last few years as it intelligently streams data in both structured and unstructured form to extract relevant information that caters in improving operational efficacy, enhancing performance management and devising vital business strategies.
While most businesses make use of various kinds of analytics, it is Big Data analytics that empowers them to get real time data to uncover latest trends and predict upcoming threats and opportunities. The erstwhile analytics methods gathered information to run analytics and derive unravelled information for taking decisions for the future. But Big Data overcomes this challenge by constantly gathering data from various data sources in several forms and helps businesses in identifying insights for taking quick decisions. Thereby, Big Data has emerged as a viable, speedy and highly efficient mode of analytics that has the potential to boost the competitiveness quotient of the business deploying it.
Big Data Analytics Is The Apt Solution For Various Verticals
Businesses in every sector want to have a competitive edge over others and this is possible through having a deep understanding about the latest market trends and preferences of the customers. This information paves the foundation for innovative business practices and stimulates smart strategy designing. Here are some of the organisations that can best leverage the potential of Big Data Analytics:-
Lately, Big Data analytics is assuming a leading role in the healthcare industry that has been depending upon the traditional relational databases for their analytics needs. Once Big Data analytics are applied, healthcare organisations can easily manage health plans, insurance information, patient records, gather information from sensor data sent to the cloud, etc. Analysing this data can help healthcare organisations in providing timely treatment to patients and can prove as a base for innovating various medical practices to improve well being of the public.
To improve public services and safety, many government agencies are now depending upon the Big Data analytics. Keeping crime rate down, introducing new regulatory policies, changes in the budget, new taxation policies, fulfilling the public amenity needs, monitoring population, etc., are crucial jobs performed by various government agencies, the efficiency of which can be improved by multi-folds owing to the implementation of Big Data analytics.
3. Travel & Hospitality
The travel and hotel industry largely survive on the customer satisfaction as it enhances their market reputation. But gauging customer satisfaction is a crucial task and for lifting the dropping customer satisfaction, they have very little time duration. With the help of Big Data analytics, these businesses can quickly analyse the large volumes of collected data and identify the problem areas to come up with unique solutions and turn the situation in their favour.
Customer service is at the core of retailers and to appeal the new age customers in the highly competitive market, retailers must have a deep understanding of the consumer behavior, their preferences and accordingly implement appropriate marketing strategies. The Big Data analytics technology helps them reach a large number of customers belonging to different demographics and target segments through collection and real time analysis of endless data derived from buying habits, customer loyalty programs, trends followed on social media sites, etc.
Technologies That Power Big Data Analytics
Big Data analytics is a vast concept and in real world implementation, several types of technology work in tandem to help businesses get maximum value from the huge collection of data. Data management, data mining, Hadoop, predictive analytics, in-memory analytics and text mining are some of the major technologies employed by Big Data analytics. These technologies aid in governing the quality of data, discovering patterns in the increasing volumes of data, storing and running applications on clusters of commodity hardware, analysing data from system memory, using statistical algorithms and machine learning for predicting future events and analysing text data from comment fields, web, books and other text-based sources.
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