Bodhtree amongst Top 20 Most Promising Business Intelligence Solution Providers in India

CIO-Review-Magazine

Bodhtree has been chosen as one among the Top 20 Most Promising Business Intelligence Solution Provider in India by the prestigious CIO Review Magazine. This acknowledgment bears witness to our dedication towards reinforcing our BI and Analytics rehearse and increasing upper hand.

CIO Review is an technology innovation magazine that shows creative venture arrangements created by developing organizations over the globe. It brings point by point profiles of a portion of the best contenders in the BI business that help ventures embrace information investigation to eventually fuel their business development. A recognized board containing achieved Indian CEOs and CIOs of open organizations, VCs, Analysts, Founders of other VC financed organizations and CIO Review’s article board on the whole select and shortlist the main 20 arrangement suppliers.

2017 List: Top 20 Most Promising Business Intelligence Solution Providers in India

Bodhtree’s profile on CIO Review: Streamlining Key Business Processes via Cloud, Analytics and Digital Deliverables

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Big Data Cloud Today! Experts discuss what today’s data is saying about tomorrow opportunities

Increased productivity, new innovations and smarter marketing are just a few advantages being realized by organizations that embrace big data.

Big Data Cloud Today!, an event held on June 7th in Mountain View, drew leaders from business and technology to discuss the next generation of Big Data use cases. Attendees to Big Data Cloud Today! learned emerging techniques, like 3d data visualization, to distill new insights from existing data.  The event addressed the growth of big data, big data architectures, and identification of new business opportunities.

As I participant in the event, I would like to share a few of the insights and key learning’s that I felt offer the most value for Bodhtree customers and network.   Milind Bhandarkar, Chief Scientist from Pivotal, Dr. Mayank Bawa, Co-President R&D Labs of from Teradata Aster, Jim Blomo Engineering Manager – Data-Mining, and Gail Ennis, CEO of Karmasphere, were a few experts who made this event truly impact full. Speakers presented first-hand experiences and lessons learned from Big Data early-adopter organizations.

Dr. Mayank Bawa (Co-President, R&D Labs, Teradata Aster) set the tone for the conference with an excellent keynote address. ‘Why is there such excitement around Big Data Analytics in the current environment?’ and ‘How are Big Data Services & Data Sciences Unique?’ were the two questions that framed his remarks.  His presentation marvelously answered them with real-life use cases in two broad categories:

• “All kinds of data in a single platform”
• “All kinds of Analytics in a single platform”

To underscore these points, he presented various applications of Big Data Solutions such as ‘Market Basket Analysis’, ’Telecom and Churn analysis’, and ‘Predictive Modeling in Insurance Domain.’ Some of the interesting takeaways, challenges and open questions are as follows:

– How will technology progress to a unified architecture from the current state?
– The focus of every company is on building a platform that bring silos of data together and facilitates seamless dataflow across systems
– Empowering data sciences and improving analytical algorithms
– Relational vs. NoSQL:
– Is there a need to build SQL layer over NoSQL?
– Does it add any business value?
– Vision of oracle, Teradata in bringing relational and NoSQL together.

How to make Big Money from Big Data? – Sourabh Satish, Security Technologies & Response, CTOs Office, Symantec

While Dr. Bawa presented the motivation to build a unified architecture with better analytics, Sourabh Satish, Security Technologies and Response at Symantec, explored the advances offered by Big Data in the Security Domain. He demonstrated some of the security tools built at Symantec and illustrated how the three fields – Big Data, Data Science and Domain Expertise – can be leveraged for building an application.

Hadoop: A Foundation for Change – Milind Bhandarkar, Chief Scientist, Pivotal

If I had to design a metric to calculate the most relevant and valuable presentation in the conference, then without a doubt the gold standard would be set by Milind Bhandarkar, Chief Scientist of Pivotal.  Mr. Bhandarkar talked about the evolution of analytics and big data and characterized by three distinct areas:

• Source Systems +ETL+EDW+Visualization
• Source Systems +Hadoop& M>R +EDW+Visualization
• Hadoop and ecosystem

He went on to explore several key issues in the Big Data field:

BI Vs. Big Data and Future
Big Data’s journey from batch processing to interactive processing. Is interactive processing possible?
Hadoop as a service?
Applications as a service?
Cloudera Impela bypassing MapReduce
Myth around how huge (Big) is the volume of data used in  analytics query (at Yahoo, Microsoft)

Why Hadoop is the New Infrastructure for the CMO (they may not know it yet!)- Gail Ennis CEO, Karmasphere

Gail Ennis talked about business use cases driving the demand for Big Data in today’s rapidly changing world, the journey of technology from BI to Big Data (predictive insights) and the potential of predictive analytics in Marketing and product Development.

Insights from Big Data: How-to? –Panel Discussion

Jim Blomo, Engineering Manager Data-Mining, Yelp
David P. Mariani, VP Engineering, Klout

The frank and energetic interaction between Professor Blomo and Mariani offered some of the most interesting discussion in the conference, including topics such as:

How to identify whether a given problem is a BI Analytics problem or Big Data problem?
Is existing BI framework needed? How Big Data evolves to be interactive BI
How a company can form a  data sciences group & their Journey in building their team
What qualities they looked at while selecting Data scientists in their team as Data Scientist is not a role well defined across the industry
Evolving technologies in data sciences and Big data (hive vs. cloudera imepala vs. shark)
Is ETL on the fly possible
Yelp and its work in data sciences
Academic  Education or Practical Experiences which helps in being a great Data Scientist

Rhaghav Karnam manages the Big Data Scientists group at Bodhtree, focusing on Big Data for customers in High Tech, Manufacturing, Life Sciences/Pharmaceuticals and government industries.  Bodhtree enables its customers and partners for business transformation through Big Data and social-mining solutions laser focused on measurable business objectives.

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Extending SAP Business Objects to All Organizational Decision-Makers

BI tools play a vital role in decision making and innovation at every level in dynamic organizations. SAP Business Objects includes tools that help expand the reach of BI Information services, enabling the organization to share, integrate and also Embed BI in applications, services, tools and business processes.

Unification of the BI data used across applications

BI can be used across multiple functions and is generally not specific to any particular department or team. It can be leveraged across applications related to finance, operations, sales or human resources. SAP Business Objects Enterprise provides a unified structure with a powerful semantic layer and integration capability that brings a “single version of the truth” to data drawn from multiple sources.

Share BI with any service-Enabled Application

To build applications that extend the advantage of a company’s BI Investment, developers can use SAP Business Objects BI Software Development Kits (SDK’s). These SDK’s can be used in any Java or .Net based application for authentication, authorization, scheduling, content display, ad hoc query, or server administration. SAP Business Objects also offers a comprehensive set of Web Services that expose BI functionality as a platform-agnostic interface. The software also supports your organization by extending the reach of BI beyond traditional corporate business.

SAP Business Objects Web Services enhances support for your tactical and operation decision making, which improves Business process efficiency.

Sridurga Vannemreddi is an SAP Business Objects and Big Data developer with Bodhtree.  For more than a decade, Bodhtree has specialized in business analytics, leveraging close partnerships with leading BI software manufacturers such as SAP Business Objects, Informatica, and IBM Cognos.  Bodhtree offers free assessments to map analytics solutions to the goals and objectives specific to your organization.

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Big Data Platform Options and Technologies

The following are the three primary architectures used to handle ‘Big Data’:

  1. Symmetric Multiprocessing Solutions (SMP)
  2. Massively Parallel Processing ( MPP) data warehousing appliances
  3. NoSQL platforms

SMP Solutions are used as the basis of most Business Intelligence / Data Warehousing storage environments. These solutions use multiple processors that share a common operating system and memory. Due to capacity limitations of the operating system architecture, these solutions often have approximately 16-32 processors. While SMP are traditionally seen as a solution for systems of online transaction processing (OLTP), the industry has recently seen demand for SMP solutions for data storage solutions and business intelligence that deal with large volumes of structured data. Increasing the power of computers and software combined with architectures designed specifically to handle large data sets have resulted in a large increase in the yield capacity of the SMP platforms.

These Data Warehousing / Business Intelligence platforms often provide shorter deadlines, are less complex to implement and support, and offer a low purchase price TCO compared to other enterprise-level data management solutions. These are ideal for data storage environments in the 5-50 terabyte range. Microsoft is a leader in this space with the launch of Microsoft SQL Server 2008 R2 Fast Track Data Warehouse platform. This platform combines database SQL Server with standard hardware manufacturers like HP and Dell in an architecture that achieves increase performance and reduce costs through traditional clustering.

The Massively Parallel Processing (MPP) platforms are built for structured data and these systems harness numerous processors working on different parts of an operation in a coordinated fashion. Since each processor has its own operating system and memory, MPP systems can grow horizontally to increase performance or capacity by simply adding more processors to the architecture. These solutions often contain 50 – 1000 processors. From a performance and cost perspective, the most important components of an MPP solution are the hardware configuration, coordination and communication between the processors. MPP solutions range from pure data warehousing appliance solutions, which offer both hardware and software in a single package, to appliance focused solutions that provide software with the option of a few different hardware configurations.

The major platform beyond SQL data management world today is NoSQL meaning “Not Only SQL.” These architectures can provide higher performance at a lower cost, with linear scalability, the ability to use commodity hardware and a free data retention scheme with no fixed data model and relaxed data consistency validation. These architectures also provide a number of different database types based on the type of data being retained. NoSQL solutions perform better in conditions where there are extremely high data volumes or high content of unstructured data such as documents and media files.

Today the most popular NoSQL platform is Hadoop. Hadoop provides an end-to-end architecture for large volumes of data, including a distributed file system (HDFS), a distributed processing manager (MapReduce) and different databases and various data flow options including Sqoop, Hive, HBase, and Pig. Hadoop can be implemented in an open source platform approach or through one of several marketed versions that can accelerate the deployment and the ability to increase support for the price of a license fee.

Sushanth Reddy is a Big Data solutions architect for Bodhtree, which specializes in analytics solutions, including data warehousing, business intelligence and Big Data.

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