SINGAPORE CLASSIFIEDS
Singapore Classified Advertisements & Listings from Singapore Expats
« Previous Ad · Next Ad »
Introduction to Big Data Analytics
With the improvements of innovations and technology over the years, organizations are now able to transform terabytes of data into actionable insights, which is nothing but big data analytics. In other words, it is a process of uncovering patterns, trends and correlations on large and diverse quantities of raw data to make data-informed decisions. In short, by big data we mean the dataset that is large in terms of volume and complexity. It is the datasets containing a large amount of diverse data, both structured as well as unstructured. Eg Bombay Stock Exchange, facebook etc. Previously, because of the sheer volume of data, traditional processing software’s were unable to handle such a huge quantity of data.
By Big Data, we mean an extremely large volume of data that comes in diverse forms and from multiple sources. For instance, every time you make online purchased, talk to a customer service representative, communicate with your virtual assistant, use your social media, emails, mobile apps, walk into a store etc., there are technologies that collects and process your data for their organization. Data is collected on a daily basis from employees, supply chains, marketing and financial teams etc.,
The process of Big Data Analytics is data collection, preprocessing, data cleaning, and analyze large datasets to identify patterns and trends to help make business decisions. Getting data into usable state takes time after collection, preprocessing, cleaning etc., Once data is ready, advanced analytics processes like data mining, predictive analysis and deep learning that turn big data into valuable trends and patterns are performed for informed business decision. For instance, by identifying the details such as customers age, gender, qualification, place, preference etc it is possible to guess the behavior of a person to target for personalized services.
With the explosion of data, big data tools like Hadoop, Spark and NoSql databases were created for storage and processing of big data, from the data collected from various sources viz., transactions, network, IoT. Sensors and more. Today, Big Data are being used with machine learning algorithms to discover and scale with complex insights.
Big Data Analytics is important because the companies can leverage their data for making improvements and optimizations across different business segments, increase efficiency, reducing costs, higher profits, handle competition, developing better customer centric products, and higher customer satisfaction.
URL : www.edujournal.com
Please Login and use the Contact User form to contact the advertiser directly.
