Earlier this month I had a great time to write Bascis of Big Data series. This series received great response and lots of good comments I have received, I am going to follow up this basics series with further in-depth series in near future. Here is the consolidated blog post where you can find all the 21 days blog posts together. Bookmark this page for future reference.
Big Data – Beginning Big Data – Day 1 of 21
Big Data – What is Big Data – 3 Vs of Big Data – Volume, Velocity and Variety – Day 2 of 21
Big Data – Evolution of Big Data – Day 3 of 21
Big Data – Basics of Big Data Architecture – Day 4 of 21
Big Data – Buzz Words: What is NoSQL – Day 5 of 21
Big Data – Buzz Words: What is Hadoop – Day 6 of 21
Big Data – Buzz Words: What is MapReduce – Day 7 of 21
Big Data – Buzz Words: What is HDFS – Day 8 of 21
Big Data – Buzz Words: Importance of Relational Database in Big Data World – Day 9 of 21
Big Data – Buzz Words: What is NewSQL – Day 10 of 21
Big Data – Role of Cloud Computing in Big Data – Day 11 of 21
Big Data – Operational Databases Supporting Big Data – RDBMS and NoSQL – Day 12 of 21
Big Data – Data Mining with Hive – What is Hive? – What is HiveQL (HQL)? – Day 15 of 21
Big Data – Interacting with Hadoop – What is PIG? – What is PIG Latin? – Day 16 of 21
Big Data – Interacting with Hadoop – What is Sqoop? – What is Zookeeper? – Day 17 of 21
Big Data – Basics of Big Data Analytics – Day 18 of 21
Big Data – How to become a Data Scientist and Learn Data Science? – Day 19 of 21
Big Data – Various Learning Resources – How to Start with Big Data? – Day 20 of 21
Big Data – Final Wrap and What Next – Day 21 of 21
Reference:Â Pinal Dave (https://blog.sqlauthority.com)
6 Comments. Leave new
Hi,
I follows your series of posts regarding the big data.
but nowhere there is a post regarding the pro and cons, how to implement it, the type of competencies to implement it / use it (DBA, programmer, analyst?);
also, what are the standards?
there is a bunch of tools, none of them appear to have a common simple language like SQL or MDX.
What’s the cost of using this compared to traditional structure data “only”? (so structure/transform sooner (traditional DW) vs later (big data))
How the big data can fit the self service BI need and trend? (most of the business analysts have problems using structure data, so I cant imagine what’s unstructured data can be for them….)
how to handle the data quality issues? its fun to gather facebook, twitter and other information, but what’s the purpose if there is no quality in the data? is it the responsibility of each developer consuming these data to do and redo the job? how to compare this to traditional ETL processes? (remember: bad data quality = bad decisions!!!)
Personally I’m a little lost on where to put the big data in an enterprise. My background is DW oriented, with huge data quality and integrity issues, so structure data is a must have.
but it was a long and great job!
continue like this :)
Personally i feel no data is a bad data. I would call the process of deriving value out of data as a science in itself (Data Science). We have done projects where in data crawling was done from various social websites and output was generated which was meaningful. Regarding hosting of Big Data in an enterprise, we went with setting up a private cloud powered by Openstack and installed hadoop framework.
Great article, i liked this article as it gives simple definition of very commonly used words like PIG, HIVE, HADOOP. I think big data in combination with IBM Watson is going to be very big thing in future.
Great article, i liked this article as it gives simple definition of very commonly used words like PIG, HIVE, HADOOP. I think big data in combination with IBM Watson is going to be very big thing in future.
hi
thank you 4 your Big Data-serial article
many useful information!
I must say a big thank you to you for the post. But i have a question, can you show an example of a working model that transform unstructured data to structured data?. Thank you