2. Meet with Big Data Cloud Experts
With over 250 individuals in attendance, all of them focused on creating and leveraging Big Data Cloud solution, the “BigDataCloud – Today!” event will be THE place to meet people and companies who share your interest in solving real-world business.

3. Don’t be Scared
Expand your knowledge base by jumping into technical deep dives with the most advanced big data cloud experts.

4. Discuss your ideas 1 to 1 with the Gurus
In-depth training classes are available in the early part of the event. Subjects covered range from MapReduce, Hadoop, Pig, Hive and others. The trainers are Gurus on their subjects and can provide real-life, in-depth information.

5. Expand your Professional Network:
This focused gathering of Big Data Cloud users, developers, industry experts, business leaders, entrepreneurs and innovative companies in leveraging “BigDataCloud – Today!” provides a unique opportunity to expand your professional network. The event is special structured to allow you plenty of opportunity to meet like minded individuals in a casual setting over snacks and wine.

6. Know the Future:
“BigDataCloud – Today!” is focused on real world solutions, and our industry experts on the panels will look into their crystal balls and forecast where the next big opportunities will lie in the future.

For the meetup on this Thursday, September 8th, for the first time, we are having an industry track. We would be looking at various Big Data solutions as practiced in sprawling industries like Healthcare, Financial & Social Gaming. So, join us at these lively discussions!

This meetup is sponsored by ZettaSet . They have recently launched a new Security Data Warehouse that enables Big Data Mining for Forensic Analysis.

Again, thanks to all of you for your support & help. If there is anything that we could do to make your experience better or enhance the value proposition of these meetups, please feel free to let me know at any time.

I am looking forward to seeing all of you on the 8th at 6:00 pm at the TechMart!

Introduction

The tool is very generic and configurable. It takes a CSV file as input and writes to HBase or Cassandra.

The CSV file could have been generated from queries on Oracle or MySQL. So it could be used to migrate data from RDBMS to NOSQL databases.

It also takes a JSON file, which defines the the mapping between the columns in the CSV and the NOSQL column family and column along with other metadata.

Here is a quick summary of the features. The terminology I am using is based on HBase.

• Loads data from CSV file.
• Mapping between CSV columns and NOSQL column family and column is provided in JSON file.
• There is many to many association between CSV column and NOSQL column family and column.
• The row key for NOSQL could be created by concatenating multiple CSV columns.
• Solr indexing of data as it’s being loaded.

The indexing feature is not implemented yet. I will be working on it next. A CSV column could be split into multiple parts and used to populate multiple NOSQL columns. On the flip side, multiple CSV columns could be consolidated to populate one NOSQL column.

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In essence, Puppet and Chef are levers used to control data center computers in a more automated fashion. The software has helped companies tap vast stores of computing power in new ways, accelerating research in fields such as financial modeling and genetics. “This really changes the way science gets done,” says Jason Stowe, the chief executive officer of Cycle Computing, a startup that uses Chef to configure thousands of computers at a time so that clients can perform calculations at supercomputer speeds. Before adopting Chef, doing such configurations took hours or even days. “We’re down to single-digit minutes now,” Stowe says.

The need for such tools originated with Google (GOOG), Amazon.com (AMZN), and their peers, who have long had to deal with the burden of managing tens or even hundreds of thousands of servers to support vast Web operations. Over the years these companies developed custom tools that can quickly turn, say, a thousand new servers into machines capable of displaying Web pages or handling sales. These programs allow the companies to run enormous, $500 million computing centers with about three dozen people at each one.

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What configuration makes sense for any given organization is driven by such ratios as the storage-to-compute ratio of your workload and other factors that cannot be answered in a generic way. Further, the hardware industry moves quickly. In this post I’ll try to outline the principles that have generally guided Hadoop hardware configuration selections over the last six years. All of these thoughts are aimed at designing medium to large Apache Hadoop clusters. Scott Carey made a good case for smaller machines for small clusters the other day on the Apache mailing list.

The key for Hadoop clusters is to buy quality commodity equipment. Most Hadoop purchasers are cost conscious and as your clusters grow, their cost can be significant. When thinking about cost, one needs to think about the whole system, including network, power and the extra components included in many high-end systems. Remember that Hadoop is built to handle component failure well and to scale out on low cost gear. RAID cards, redundant power supplies and other per-component reliability features are not needed. Buy error-correcting RAM and SATA drives with good MTBF numbers. Good RAM allows you to trust the quality of your computations. Hard drives are the largest source of failures, so buy decent ones.

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IBM has announced an agreement to acquire i2 to accelerate its business analytics initiatives and help clients in the public and private sectors address crime, fraud and security threats.

Financial terms of the deal were not disclosed.

i2, with more than 4,500 customers in 150 countries, is a provider of intelligence analytics for crime and fraud prevention based in Cambridge, U.K., with U.S. headquarters in McLean, Va. i2′s clients span multiple sectors globally such as banking, defense, health care, insurance, law enforcement, national security and retail. i2′s solutions are currently used by 12 of the top 20 retail banks globally and eight of the top 10 largest companies in the world.

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The report is based on responses from 325 IT managers, business users and consultants at small, medium and large companies.

Slightly more than a third of the respondents said they are currently running some form of advanced analytics on big data — mostly for business intelligence, predictive analytics, data mining and statistical analysis tasks.

Close to 45% of those surveyed expect that big data analytics will enable more accurate business insights while 38% are looking to use the technology to better recognize sales and market opportunities better. More than 60% are hoping that big data analytics can boost their company’s social media marketing capabilities.

The fastest growing use case for big data analytics is advanced data visualization, according to the TDWI survey. A growing number of companies are running sophisticated analytics tools on big data sets in order to build highly complex visual representations of their data.

“Big data used to be a technical problem when companies were struggling to deal with the management of large volumes of data,” said Philip Russom, a TDWI analyst and author of the report. “Now, if you apply analytics to it, there is a lot that can be gained from big data, that you could not get” from traditional BI and data warehousing technologies.

The term “big data” refers to very large data sets, often hundreds of terabytes or petabytes in scale. Increasingly, the term is used to describe not just large volumes of structured data but also unstructured data such as weblogs, clickstream data, machine and sensor data and social media data.

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• Strata Jumpstart, 9/19, New York Marriott Marquis – A daylong crash course for managers, strategists, and entrepreneurs on how to manage the data deluge that’s transforming traditional business practices.
• Strata Summit, 9/20-9/21, New York Marriott Marquis – Two days on the essential high-level strategies for thriving in “the harsh light of data,” delivered by the battle-tested business and technology pioneers who are leading the way.
• Strata Conference, 9/22-9/23, New York Hilton – Two days of the nuts-and-bolts needed for building a data-driven business—the latest on skills, tools, and technologies you need to make data work.

Register for a Super Pass, which gives you access to the whole week of conference and evening events, at a reduced rate.

BigDataCloud readers get a 30% discount. Use discount code DataCloud.