Business data has existed for ages. It can be scrutinized in the form of handwritten ledgers, account books, customer information forms, customer reference forms, etc. A large amount of this data collected goes unnoticed. Small / Medium sized entrepreneurs believe that Big Data is for big companies, they have nothing to do with it. They feel that implementing Big Data technologies will result in huge financial burdens for the company.

Big Data does threaten to create a divide between the big businesses and small businesses. Big companies have the advantage of data crunching; whereas small businesses are thrown back in dark Stone Age.  At times, they find it difficult to decide about the Big Data and Analytics while looking at ways to keep up with bigger competitors.
The following points are to be considered whenever small businesses plan to fall in the Big Data pool.

• Simplicity: The solution should be easy to use and synchronised with the functioning of the system at large. The business users should be ableto use it without need of specialists being involved every time. This could be done by setting up something like Oozie workflow which once setup could update the data incrementally.
• Flexibility: The small businesses wish to adopt a technology, which allows elasticity in operations. The solution should integrate with the existing systems. The vendor shouldn’t force the entire solution package to the company but allow them to choose according to their requirements. With Hadoop having large set of supported Apache projects gives lot of choices to pick up tools based on end user requirements.
• Cost:The solution has to be cost effective. The license agreements should have a window for expansion as and when requirement arises. An affordable Big Data solution to serve small businesses is the need of the hour. Hadoop cluster could be built upon commodity machines without using expensive servers with negligible or no software costs. The companies can also use open source software tools for big data analytics there by reducing the costs involved.

For instance, a grocery store in the neighbourhood can utilise big data Analytics to understand the customer buying patterns (quantity purchased, variety of food items, pricing affects the buying quantity, etc.) and procure the quantities accordingly. Once these small businesses manage to obtain the data the next step involves encouraging employees to utilize this data in a competitive manner.

The positive differences Hadoop can make for small businesses include:

• Archive: Instead of taking old data offline or purge it to keep the current system lightweight, the data could be archived on Hadoop cluster which will keep your live application fast and the data is still available for back tracing and analytical purpose.
• Existing Skill set: There are many ways to query and analyse the data on Hadoop cluster which does not require updating the skill set on large extent. Users can use Hive Query Language as SQL, Apache Pig for scripting interface and MapReduce for programming. These are quite similar to commonly used programming platforms.
• Free BI Tools: Dashboards and reports can be generated using free reporting tools like JasperSoft, Pentaho. They provide customized critical insights for local business/region which are otherwise unavailable.
• Linear Scalable: Hadoop helps add more nodes to existing cluster without increasing burden, and improve performance implying the cluster stays updated.

In this way Small businesses can utilise Hadoop to realise their Big Data dreams.
Image Courtesy: sparkblog.emc.comBusiness data has existed for ages. It can be scrutinized in the form of handwritten ledgers, account books, customer information forms, customer reference forms, etc. A large amount of this data collected goes unnoticed. Small / Medium sized entrepreneurs believe that Big Data is for big companies, they have nothing to do with it. They feel that implementing Big Data technologies will result in huge financial burdens for the company.
Big Data does threaten to create a divide between the big businesses and small businesses. Big companies have the advantage of data crunching; whereas small businesses are thrown back in dark Stone Age.  At times, they find it difficult to decide about the Big Data and Analytics while looking at ways to keep up with bigger competitors.
The following points are to be considered whenever small businesses plan to fall in the Big Data pool.

• Simplicity: The solution should be easy to use and synchronised with the functioning of the system at large. The business users should be ableto use it without need of specialists being involved every time. This could be done by setting up something like Oozie workflow which once setup could update the data incrementally.
• Flexibility: The small businesses wish to adopt a technology, which allows elasticity in operations. The solution should integrate with the existing systems. The vendor shouldn’t force the entire solution package to the company but allow them to choose according to their requirements. With Hadoop having large set of supported Apache projects gives lot of choices to pick up tools based on end user requirements.
• Cost:The solution has to be cost effective. The license agreements should have a window for expansion as and when requirement arises. An affordable Big Data solution to serve small businesses is the need of the hour. Hadoop cluster could be built upon commodity machines without using expensive servers with negligible or no software costs. The companies can also use open source software tools for big data analytics there by reducing the costs involved.

For instance, a grocery store in the neighbourhood can utilise big data Analytics to understand the customer buying patterns (quantity purchased, variety of food items, pricing affects the buying quantity, etc.) and procure the quantities accordingly. Once these small businesses manage to obtain the data the next step involves encouraging employees to utilize this data in a competitive manner.
The positive differences Hadoop can make for small businesses includes:

• Archive: Instead of taking old data offline or purge it to keep the current system lightweight, the data could be archived on Hadoop cluster which will keep your live application fast and the data is still available for back tracing and analytical purpose.
• Existing Skill set: There are many ways to query and analyse the data on Hadoop cluster which does not require updating the skill set on large extent. Users can use Hive Query Language as SQL, Apache Pig for scripting interface and MapReduce for programming. These are quite similar to commonly used programming platforms.
• Free BI Tools: Dashboards and reports can be generated using free reporting tools like JasperSoft, Pentaho. They provide customized critical insights for local business/region which are otherwise unavailable.
• Linear Scalable: Hadoop helps add more nodes to existing cluster without increasing burden, and improve performance implying the cluster stays updated.

In this way Small businesses can utilise Hadoop to realise their Big Data dreams.
Image Courtesy: sparkblog.emc.com[:]