What are the challenges of big data? How can organizations use its benefits to generate ROI?
"Vaishnavi Agrawal gives an overview of everything big data - from customer relationship management to fraud detection and cost reduction.
Data is growing rapidly in every sector.
Big data, cloud computing, Internet of Things, and data science are the chief trending technologies that are deriving innovation and transformation throughout the world. Though all these technologies differ from each other in several aspects, it's hard to talk about one without the other.
Big data and data science are closely entwined in such a way that there is a myth about both being the same. While data science deals with data cleansing, data preparation, and data analysis, big data is used for analyzing insights which will be used for better decision-making and strategic business moves..."
Data management is a very broad term. Here's a few best practices to consider
"In my experience with storage and databases, data management is a very broad and loosely used term. For instance, if you want to build data for performance reasons, being able to move the data between spinning media and higher performance media (without the application knowing) could be data management, and it's the job of the infrastructure to do so. When looking at systems, anything that is implicitly 'scale out' and is designed to run across hundreds or thousands of nodes must have the capability to guarantee multiple copies in the event of hardware, disk, or network failures..."
Spark is the ideal big data tool for data-driven enterprises because of its speed, ease of use and versatility. It will help you understand your data quickly and help you make informed decisions faster
"Apache Spark is a fast data processing framework dedicated to big data. It allows the processing of big data in a distributed manner (cluster computing). Very popular for a few years now, this framework is about to replace Hadoop. Its main advantages are its speed, ease of use, and versatility.
Apache Spark is an open source big data processing framework that enables large-scale analysis through clustered machines. Coded in Scala, Spark makes it possible to process data from data sources such as Hadoop Distributed File System, NoSQL databases, or relational data stores like Apache Hive. This framework also supports In-memory processing, which increases the performance of analytical applications of big data. It can also be used for conventional disk processing if the data sets are too large for system memory..."
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