Hi Hitesh,

1. Some analytics platforms that I believe can help you unveil your big data:

- 1010data

https://www.1010data.com/company

- Actian

http://www.paraccel.com

- Amazon Web Services

http://aws.amazon.com

- Cloudera

http://www.cloudera.com/content/cloudera/en/home.html

- HAVEn (HP)

http://www8.hp.com/us/en/software-solutions/big-data-platform-haven/index.html

- Hortonworks

http://hortonworks.com

- IBM's

http://www.ibm.com/smarterplanet/us/en/ibmwatson/

- Infobright

https://www.infobright.com

- Kognitio

http://www.kognitio.com

- MapR

https://www.mapr.com

- Microsoft

http://www.microsoft.com/en-us/server-cloud/solutions/big-data.aspx

- Oracle

https://www.oracle.com/big-data/index.html

- Pivotal

http://pivotal.io

- SAP

http://go.sap.com/solution/big-data.html

- Tableau

http://www.tableau.com

- Teradata

http://www.teradata.com/?LangType=1033

- VoltDB

http://voltdb.com/?n=a&utm_expid=66808973-1.O562mQS1TnKG3RbsGkKu5Q.1

2. To start looking at your data I would recommend one solution with a user-friendly visual environment with no(t so much) programming requirements:

- Orange: open source data mining package;

http://orange.biolab.si

- Weka: an open source stats and data mining library;

http://www.cs.waikato.ac.nz/ml/weka/

- RapidMiner: an open source statistical and data mining package;

https://rapidminer.com

2.1 After answering some of your first questions try to jump to a more script-based solution; on that stage I would look into:

- Scikit Leran

http://scikit-learn.org/stable/

3. Some good resources to start from (from my experience).

Python oriented:

- Programming Collective Intelligence http://shop.oreilly.com/product/9780596529321.do

Very popular among beginners with real-life examples (data)

Many Python examples

- Machine Learning an Algorithmic Perspective

http://www.amazon.com/Machine-Learning-Algorithmic-Perspective-Recognition/dp/1420067184

Mainly focused on algorithms

Not so much math and many Python examples

- Machine Learning in Action

http://www.amazon.com/Machine-Learning-Action-Peter-Harrington/dp/1617290181

Similar to the latter; algorithm hands-on

Many Python examples

Weka (platform) oriented:

- Data Mining: Practical Machine Learning Tools and Techniques

http://www.cs.waikato.ac.nz/ml/weka/book.html

Very good introduction on ML

It is a companion book for the Weka platform

I would also look into:

- Tom Mitchell's book - Machine Learning (1997) - and online material

http://www.cs.cmu.edu/~tom/

- Christopher Bishop's - Pattern Recognition and Machine Learning (2007)

http://www.springer.com/gp/book/9780387310732

- Jason Brownlee's - Machine Learning Mastery web page.

http://machinelearningmastery.com

I hope it helps - good luck!

I prefer R programming for big data

Thanks.

What are PIG and HIVE?

http://stackoverflow.com/questions/3356259/difference-between-pig-and-hive-why-have-both

Hallo,

           PIg and HIVE are used when you are interested to perform analysis on HDF file. if you have CSV file then first perform analysis on R and Weka which will gave you better way of exploration. You can also used RapidMiner. PIG and HIVE does not gave you algorithm based data Exploration!

You are welcome for any more concern.

Regards

Muddsair

Rapidminer

PIG+HIVE+R{WITH ITS PACKAGES}+PYTHON{WITH ITS PACKAGES}

SPSS and R-Programming

Thanks all for your great help to start work on Big Data. I look forward and if find any discrepancy then contact individual.

Thanks again

NSA ... just go online and fill the application forms. https://www.nsa.gov/

Thanks Muhammad Habib ur Rehman,

Thanks for your clear formation and start my work on Big data. I know python well so i'll start on it.

And also thanks for publication list. It will help me to improve my knowledge on Big Data.

@Wieslaw Krawcewicz: Thanks so much Wieslaw Krawcewicz. What i need to do now? i have already filled application form in career -> apply now.

Can you please tell me what's next?

Rapid Miner & SAP HANA

Big data are very likely to be heavy-tailed, so head/tail breaks is a useful tool; see examples in the following papers:

Jiang B. (2015), Head/tail breaks for visualization of city structure and dynamics, Cities, 43, 69-77, Preprint: http://arxiv.org/ftp/arxiv/papers/1501/1501.03046.pdf

Jiang B. and Miao Y. (2014, accepted), The evolution of natural cities from the perspective of location-based social media, The Professional Geographer, xx(xx), xx-xx, DOI: 10.1080/00330124.2014.968886,  Preprint: http://arxiv.org/abs/1401.6756

https://www.researchgate.net/publication/283017967_Big_Data_Is_not_just_a_New_Type_but_a_New_Paradigm

Research Big Data Is a New Paradigm

Hi Hitesh,

1. Some analytics platforms that I believe can help you unveil your big data:

- 1010data

https://www.1010data.com/company

- Actian

http://www.paraccel.com

- Amazon Web Services

http://aws.amazon.com

- Cloudera

http://www.cloudera.com/content/cloudera/en/home.html

- HAVEn (HP)

http://www8.hp.com/us/en/software-solutions/big-data-platform-haven/index.html

- Hortonworks

http://hortonworks.com

- IBM's

http://www.ibm.com/smarterplanet/us/en/ibmwatson/

- Infobright

https://www.infobright.com

- Kognitio

http://www.kognitio.com

- MapR

https://www.mapr.com

- Microsoft

http://www.microsoft.com/en-us/server-cloud/solutions/big-data.aspx

- Oracle

https://www.oracle.com/big-data/index.html

- Pivotal

http://pivotal.io

- SAP

http://go.sap.com/solution/big-data.html

- Tableau

http://www.tableau.com

- Teradata

http://www.teradata.com/?LangType=1033

- VoltDB

http://voltdb.com/?n=a&utm_expid=66808973-1.O562mQS1TnKG3RbsGkKu5Q.1

2. To start looking at your data I would recommend one solution with a user-friendly visual environment with no(t so much) programming requirements:

- Orange: open source data mining package;

http://orange.biolab.si

- Weka: an open source stats and data mining library;

http://www.cs.waikato.ac.nz/ml/weka/

- RapidMiner: an open source statistical and data mining package;

https://rapidminer.com

2.1 After answering some of your first questions try to jump to a more script-based solution; on that stage I would look into:

- Scikit Leran

http://scikit-learn.org/stable/

3. Some good resources to start from (from my experience).

Python oriented:

- Programming Collective Intelligence http://shop.oreilly.com/product/9780596529321.do

Very popular among beginners with real-life examples (data)

Many Python examples

- Machine Learning an Algorithmic Perspective

http://www.amazon.com/Machine-Learning-Algorithmic-Perspective-Recognition/dp/1420067184

Mainly focused on algorithms

Not so much math and many Python examples

- Machine Learning in Action

http://www.amazon.com/Machine-Learning-Action-Peter-Harrington/dp/1617290181

Similar to the latter; algorithm hands-on

Many Python examples

Weka (platform) oriented:

- Data Mining: Practical Machine Learning Tools and Techniques

http://www.cs.waikato.ac.nz/ml/weka/book.html

Very good introduction on ML

It is a companion book for the Weka platform

I would also look into:

- Tom Mitchell's book - Machine Learning (1997) - and online material

http://www.cs.cmu.edu/~tom/

- Christopher Bishop's - Pattern Recognition and Machine Learning (2007)

http://www.springer.com/gp/book/9780387310732

- Jason Brownlee's - Machine Learning Mastery web page.

http://machinelearningmastery.com

I hope it helps - good luck!

Hello 

There are lots of tools available for the Big Data analysis..

like a

GRIDGAIN 

JASPERSOFT

UPSIGHT

Karmasphere

Infochip Cloud. 

for more details please check it out this paper..

http://ir.inflibnet.ac.in/handle/1944/1890

I did a course on TABLEAUX and I reckon it is pretty good. 

Hi,

This is a comparison between R and Python made by DataCamp.