Where do we use Hadoop Big Data mostly
Data analytics plays a major role in most organizations as it acts as a guide for future strategy with a clearer vision. Hadoop is the leading and most comprehensive open source technology for big data solutions. It is preferred equally by SMEs and major MNCs, private and public sector institutions as an option for deciphering the trends that data reveals.
Where is Big data Generated?
Big data is a compilation of data gathered from sources that are fuelled by the internet – from social media, search engines, click-through-rates, surveys and much more. Big data is used for improving marketing efficiency and raising profitability by spotting trends in the retail industry through seeing customer preferences. In the health sector, it is used for computing issues, tracking solutions and finding cause and effect links. Inputs from various sources are rendered complete by the various analytical tools and further presented in an easy to understand manner for decision-making.
Where is Big data mostly used?
Big data is a source of information that is used by companies across all industries – retail, finance, real estate, information technology and so forth. As businesses are beginning to understand the importance of unravelling the mysteries that are hidden under the immense data sets, they are rapidly adopting technologies that will keep pace with the rate at which data is generated. With digitization, as rapidly as data is generated, it is being rendered obsolete at the same pace too. Hence, it is essential to have a rapid response ready.
Where does Hadoop step in for Big Data?
Hadoop has had a profound impact on making big data analytics tools accessible to a vast array of businesses. It's open source architecture, thriving developers’ forum and user-friendly tools make it easy to integrate with existing systems in the business workplace. For companies that have to watch how much they invest on technology, Hadoop offers all the advanced features at a very small development price. A few places where Hadoop is used are:
- Active data archive – Hadoop is appropriate for storing and cross-linking transactional, sensor machine, clickstream and social media data among others. Its powerful archive allows the user to access data at a later date when the information is critical.
- Analyse that – Hadoop’s design, which enables it to easily manage large volumes of data in all sizes and forms, also allows it to run analytical algorithms. These can be presented into graphs and charts for understandable presentations.
- Managing large data sets on vastly distributed nodes – The Hadoop Distributed File System (HDFS) is designed to plug any nodal failure to ensure seamless data streaming and mix fault tolerance with high throughput.
- Managing multiple systems – Hadoop has a tool called “zookeeper” that manages access of multiple data clusters across machines. This enables the user to synchronize their work across the different machines.
Hadoop is already the favourite platform for data management amongst major businesses, from varying industries. Whether the nature of data is simple or complex, Hadoop is leading the market by a huge margin.
About the Author:
Sonal Maheshwariloves pursuing excellence through writing and has a passion for technology. She has successfully managed and run personal technology magazines and websites. She currently writes for intellipaat.com, a global training company that provides e-learning and professional certification training.
The courses offered by Intellipaat address the unique needs of working professionals. She is based out of Pune and has an experience of 6 years in the field of content writing and blogging. Her work has been published on various sites related to Hadoop, Big Data, Business Intelligence, Project Management, Cloud Computing, IT, SAP, Project Management and more.
Even though we hear lot of hype on BigData but real life implementations are very few. Lot of small to medium companies are unable to have a case study to implement. And also there are lot of BigData tools out in the market such as hadoop, sap hana and datapower and most of them have very few successful implementations
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