This is a Part 2 Follow-Up post of Questions & Answers asked by our trainees in Big Data Hadoop Administration Webinar in which we have covered Introduction of Big Data, What Is Big Data & 4 V’s, Big Data Use Cases, Big Data Types: Structure, Un-Structured & Semi-Structured and much more.
We recently had a Masterclass on Big Data Hadoop Administration covering What, Why & How. In that webinar, there were a lot of questions. Most of these questions were answered in Webinar however not all questions were covered because of time. We’ll be adding these questions over a period of time in Private Facebook Group for BigData & Hadoop and will also post these questions with answer in our blog.
These are the few more questions, which we feel is common to everyone, so we have chosen these question asked by the attendees during the webinar.
This is the follow-up blog of our previous post in which we have covered remaining Q/A’s asked during the webinar
Q. What is the Role of Bigdata & Hadoop in Machine Learning & Artificial Intelligence?
Machine Learning and Big Data as such have no direct relation. Although one can say that Big Data Techniques can be used in Machine Learning. I will tell you the difference between both the fields for you to understand better. Machine Learning usually works with huge chunks of data and this where Big Data comes into the picture.
Machine learning: Machine Learning is the science of creating algorithms and program which learn on their own. Once designed, they do not need a human to become better.
Some of the common applications of machine learning include the following:
- Web Search
- Spam filters
- Recommender systems
- Ad placement
- Credit scoring
- Fraud detection
- Stock trading
- Computer vision
- Drug design
Machine learning helps data science by making a provision for data analysis, data preparation and even decision making like real-time testing, online learning. Data science clubs together algorithms derived from machine learning in order to provide a solution. Data science carries out this activity by taking a lot of ideas from basic mathematics, statistics and domain expertise.
Big Data Analytics: Big Data Analytics is studying large data sets (big data) to identify hidden patterns, market trends, consumer preferences and other valuable information helping organizations to form strategic business decisions.
With the help of Big data analytics, data scientists and other analytics professionals can examine huge amounts of structured data as well as the untapped data by deploying analytics and business intelligence.
Big Data Analytics comprises specialized software and analytics systems benefiting business in many ways like
- Cost efficiency: Hadoop and cloud-based analytics are big data analytics technologies are very cost effective when storing huge amounts of data. Moreover, this also helps in finding more effectual ways of doing business.
- Faster decision making: Organizations can examine data immediately with superfast Hadoop and in-memory analytics. Decisions can be taken with much ease on the basis of what they have experienced.
- New products and services: Big data analytics helps to easily understand consumer needs and preferences giving more power to serve customers what they want.
Q. How BigData is Evolving Now a Days? What is the Future scope?
For the last five years or so one could argue that “big data analytics”, or any of the semantic variations thereof, has been the hottest sector in the silicon valley. The Internet of Things could make a claim to that crown now, but really the most interesting thing about The Internet of Things is all the data, and so we’re right back to big data and analytics, which is a part of big data.
Data in aggregate is growing so fast that everything about how we think about data now is going to change radically in the next ten years. If you’re a software engineer or work in technology in any way, this should sound like an opportunity. Everything from hardware to networking to database technology to presentation layer is already changing rapidly to allow us more efficient access to data that will let us live and work better.
When I hear terms like big data analytics or cloud, they’re being used often enough and to describe companies small or obscure enough that they don’t really mean anything. This is a general knock against buzzwords and the nature of search engine marketing and the semantics of new technology and hype-waves in general.
But don’t let that fool you. For people who make decisions about how to allocate resources, big data analytics is one of the more important wormholes through which computing power and networking capability transform into honest to god Quality of Life” improvement that’s so significant it defies our attempts to measure it.
According to a report, the market for, more specifically the Business Intelligence Market is expected to grow to $20.81 Billion by 2018.
The sudden Business Intelligence growth is influenced by many factors. like,
- Organisations are increasingly tapping opportunities to leverage streaming data generated by devices, to make faster, relevant and real-time decisions.
- Data Analytics will include Cloud Deployments of BI and Data Analytics platforms which have the potential of reducing the cost of ownership and aid speedy deployment.
- There is also a need for business users to analyze, large and complex combinations of the data source and data models. This needs to be done faster than before, in a more automated method for expanded use.
These are one of the few questions which were asked during our webinar on Big Data Hadoop Administration covering What, Why & How. If you have any question related to Big Data, you can either ask by commenting on the blog or just write back to us at email@example.com
You will get to know all of this and deep-dive into each concept related to BigData & Hadoop, once you will get enrolled in our Big Data Hadoop Administration Training
Related /Further Readings
If you are just starting out in BigData & Hadoop then I highly recommend you to go through these posts below, first:
- Big Data Hadoop Keypoints & Things you must know to Start learning Big Data & Hadoop, check here
- Big Data & Hadoop Overview, Concepts, Architecture, including Hadoop Distributed File System (HDFS), Check here
- Hadoop Distribution: Cloudera vs Hortonwork Check here
Next Task For You
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