Big Data Training for Managers

Introduction to Big Data and its tools is mandatory for decision-makers. Understanding the needs and challenges of Big Data technology, during implementation and the know-how of moving the organization from traditional data storage sources to big data is pivotal for business success.

Learn about the open-source distributed computing framework developed to handle Big data. Hadoop framework makes the developer’s job very easy by managing the resources & the data in the cluster automatically. This gives the developers the freedom to focus on the business rather than the infrastructure. Hadoop is a very easy plug & play architecture that can be scaled up as the requirement increases. There are a lot of High- level projects developed on top of Hadoop to take advantage of the distributed framework of Hadoop. Learn about these features & the tools used predominantly in the industry to handle huge amounts of complex data.

If businesses have to survive and excel then they have to adopt technology & leverage on Big data. Analytics is a study to process the data & derive hidden truths/insights to provide the management a chance to mitigate the risk by predicting these risks upfront & also enhance customer satisfaction and retention. In order to churn a huge amount of complex data generated by enterprises, specialized tools are required. Tools which are capable to handle the real-time data which can be of any form structured or unstructured and of huge size.

Apache Spark is a new age tool that is a distributed computing framework designed to attain speeds that are lacking in MapReduce framework tools. Spark achieves the speed by keeping the data in-memory as much as possible on the cluster nodes. Spark is also known as a Unified stack and it has language flexibility. Learn about the libraries used for using Spark with Python (PySpark) and R (Spark). Understand the detailed functionality of Spark components: Spark Core, Spark SQL, Spark Streaming, Graphix, and MLlib. Learn about the unique data abstraction of Spark known as RDD and Spark operations on RDD’s.

Big data is a word that describes the sheer size of the data and the complexity of handling the data. It can be described using 4 Vs: volume, variety, velocity, and veracity. The traditional tools and techniques are not sufficient to deal with the complex huge and varied types of data in real-time. We need specialized tools designed to handle Big data for enterprises. The majority of these tools are open source and free to explore by any individuals. Understanding the Big Data tools and technology will help you in taking necessary steps when required to assist the business take advantage of the humongous amount of data available.

Cloud service is one of the hottest trends which has many advantages compared to traditional in house servers. Cloud computing is a technology to share unlimited computer resources over the internet instead of maintaining personal resources or in-house servers to run services. Cloud computing can be explained as service to store, process and access data through the internet. Cloud platforms have many advantages like cost Savings, high Speed, back-up and restore data, automatic software integration, reliability, and the most important for Big data is unlimited storage capacity. Cloud Infrastructure is the perfect fit for the requirements of Big data.

Businesses across the globe are increasingly focusing on taking advantage of deriving answers from the past. Big data analytics projects are initiated to solve business problems. Trying to dig into huge amounts of organization data to find patterns or hidden anomalies will give actionable insights. Analyzing Big data can boost enterprise sales, increase their efficiency, and improve operations, customer service, customer satisfaction, customer retention, and risk management. This will help enterprises to gain a competitive advantage over others. Learn about applications of Big Data Analytics in various sectors which give a huge commercial benefit to the businesses.