Is Big Data As A Service (BDaaS) For The Enterprise: A Real Badass Idea Or What?

As the sheer volume of unstructured data generated on a regular basis continues to grow exponentially — ethics and efficacy of big data is a concern. In 2010, the world’s data volume passed one zettabyte (1 billion terabytes) and by 2015, the estimated global volume will be about eight zettabytes.

According to a research published by International Data Corporation, the worldwide market for Big Data technology and services forecast is expected to grow 40% per year (compounded) –  from $3.2 billion in 2010 to almost $17 billion in 2015.

The most merciful thing in the world, I think, is the inability of the human mind to correlate all its contents. – H.P. Lovecraft, “The Call of Cthulhu,” 1928

So we come to Big Data and Big Data-As-A-Service!

From my perspective, this is an erroneous analysis of the market opportunity. Why?

“Big data-as-a-service” (BDaaS) is a delivery platform of predictive statistical analysis tools by an outside vendor that helps your company to better understand and use insights gained from large information sets in order to create an edge over your competitors.
Big data-as-a-service is a form of managed services, similar to Software as a Service (SaaS), Infrastructure as a Service (IaaS), Platform as a Service (PaaS) or Infrastructure as a Service (IaaS) and often relies upon cloud storage.

Looks interesting and worth keeping an eye on.

But, the bottom line is, is everybody ready for “Big data-as-a-service” (BDaaS)?

According to a recent Gartner report, 42% of all IT leaders have either already invested in Big Data technology, or will be in the very near future.  There are not many vendors in the IT industry that have not developed some kind of Big Data solution. However, here are some great Big Data-as-a-Service (BDaaS) solution Providers to watch:

IBM – Big Data Ecosystem : IBM is unique in having developed an enterprise class big data platform that allows you to address the full spectrum of big data business challenges. IBM is the only vendor with this broad and balanced view of big data with the needs of a platform – the benefit is pre-integration of its components to reduce your implementation time and cost.

The key platform capabilities include:
– Hadoop-based analytics: Processes and analyzes any data type across commodity server clusters.
– Stream Computing: Drives continuous analysis of massive volumes of streaming data with sub-millisecond response times.
– Data Warehousing: Delivers deep operational insight with advanced in-database analytics.
Supporting platform services:
– Accelerators: Faster time to value with pre-packaged analytical and industry-specific content.
– Application Development: Streamline the process of developing big data applications.
– Information Integration and Governance: Integrate, protect, cleanse, govern, and deliver your trusted information
– Systems Management: Monitor and manage your big data system for secure and optimized performance.
– Reference Architectures: Hardware, networking and system software blueprints to accelerate time to value.
Analytic Applications:
– Business Intelligence: Enables business users to access and analyze the information they need to improve decision making, gain better insight and manage performance.
– Predictive Analytics: Uncover hidden patterns and relationships in Hadoop data that can be used to accurately predict business outcomes.

Intel Big Data Analytics : The Intel Distribution for Apache Hadoop software is the only distribution built from silicon up to enable the widest range of data analysis on Apache Hadoop. It is the first with hardware-enhanced performance and security capabilities. It is the only open source platform for big data with support from a Fortune 100 company. Intel is committed to developing a platform on which the entire ecosystem can build next-generation analytics solutions.

HP Telco Big Data and Analytics : HP helps you gain actionable insight into usage patterns, preferences and interests in a real-time context, whether data is structured or unstructured. The insight can help you identify new services to offer, create new revenue streams and optimize your existing network investments.

The HP Telco Big Data and Analytics Solution addresses four main areas:
Targeted product and marketing offers – gain complete contextual insight into your customers’ needs then take action to improve customer satisfaction and achieve better retention rates.
Network optimization – improve your capital planning and user experience via optimized network utilization and real-time response to traffic congestion situations.
New business model enablement – capture the real-time business value of each of your customers and leverage it via new collaborative business models.
Proactive data strategies – manage large amounts and varieties of data in a cost-efficient way, securely available to the whole enterprise.

Oracle – Oracle Engineered Systems ship pre-integrated to reduce the cost and complexity of IT infrastructures while increasing the productivity and performance of your data center. We can shorten time to value for your big data initiative and decrease risk. Hidden in all the new volumes and varieties of big data is the information you need to grow revenue, cut costs, and innovate. Big data can transform your business, but you have to uncover that new insight with big data analytics.

Cloudera Hadoop & Big Data  – The cost-effectiveness, scalability and streamlined architectures of Hadoop will make the technology more and more attractive. In fact, the need for Hadoop is no longer a question. The only question now is how to take advantage of it best, and the enterprise-proven answer is Cloudera.

Enterprise Hadoop : Hadoop is an enterprise viable data platform and that the most effective path to its delivery is within the open community. Enabling the next generation of big data processing through a multi-application data platform that enables multiple processing paradigms from batch to interactive, realtime and more

Teradata : Teradata can help you manage this onslaught with big data analytics for structured big data within an integrated data warehouse– and now the Teradata Aster Discovery Platform can help you deal with the emerging big data that typically has unknown relationships where fast analytic iteration is required to unlock new insights. Together, these two powerful analytic platforms provide the two key systems for a unified data architecture for smarter, faster, decisions.

ClickFox  – ClickFox CEA focuses exclusively on customer behavior across the enterprise, identifying and modeling the actual path taken for every customer interaction. Our patented technology aggregates this data, assigning unique behavioral codes to each interaction across all customers and all touch points to produce a powerful and dimensional visualization of customer experience across the enterprise.

1010data  –  With the power and scalability of 1010data’s Cloud-based platform, companies no longer need to build and maintain their own on-site data warehouses. Such projects are typically big, expensive and risky, and the bigger the data, the bigger the cost and risk.

Tresata : TREE has become a pre-requisite and ‘must-have’ big data capability for any company that wishes to monetize their ever expanding data assets, especially as they pour it all into hadoop.  and it gets better. tresata was the first analytics software company to completely architect every single piece of its software on hadoop.  hadoop, which has since become the de-facto operating system to manage really large data (we actually coined the term ‘Data Operating System’ to refer to it), offers scale, speed and cost advantages that are impossible to match with any other data or analytics system.

Datameer : Datameer is the only analytics application that scales with your needs. Empower users to work independently, in a group, or across the company. Develop on your laptop, test with your work group, deploy to your company and scale with your needs: on your laptop, server or cluster.

HPCC  –  A benefit for customers using the HPCC is that you could gain access to LexisNexis Risk Solutions vast amounts of data, including people, businesses, assets, and much more. This is available only to Enterprise Edition customers and requires additional due diligence and entitlement processes.   Cloud to cloud access via the HPCC Systems Private Data Cloud at “Cloud-To-Cloud Speeds.” Using our HPCC Systems Private Data Cloud, you can analyze terabytes of data and uncover value you never knew you had.

Datastax – DataStax Enterprise empowers you to put more of your big data to work for your business faster than any other alternative. It seamlessly integrates best-of-breed technologies for real-time data with Apache Cassandra, batch analytics with Apache Hadoop, enterprise search with Apache Solr and visual monitoring and management with OpsCenter. It extends Cassandra’s big data functionality and continuous availability to deep analytics and search workloads simultaneously within the same database cluster.

Splunk  – Splunk Enterprise is the leading platform for collecting, analyzing and visualizing machine data. It provides a unified way to organize and extract real-time insights from massive amounts of machine data generated across diverse sources. You can try Splunk Enterprise for free. It’s easy to deploy and use so you can turn your data into insights in minutes and hours, not months or years. And it scales as your needs grow – from a single server to multiple data centers.

Infosys BigDataEdge  – Infosys BigDataEdge enables real-time discovery of data across both internal systems and external sources such as Twitter, Facebook, etc. The Discovery and Aggregation module comes with over 50 pre-built connectors to leading enterprise systems, enabling rapid discovery of relevant data. It delivers rich and rapid insights to enterprises.

Real-time Data Discovery
– Improve data extraction and processing time by 40%
– Accelerate the enterprise’s ability to extract information from new data sources

Develop Rich and Rapid Insights
– Enable the enterprise to generate insights up to 8 times faster
– Choose from a range of comprehensive and rich visualization options (over 50)
– Benefit from ready-to-use custom dashboards and more than 250 proven algorithms

Action decisions
– Collaboration Wall to enable faster decision-making around insights
– Rapid operationalization of decisions across the enterprise systems

You can also watch a Bangalore-based firm PromptCloud, dealing with large-scale data crawl and extraction and offers big data solutions using its cloud computing solutions on a customized basis. Service Offerings: Deep data crawls- all past data on the site, Structured data feeds- daily/weekly/n times a day, Ability to supply only incremental data, Crawling data from AJAX/non-AJAX based sites, Platform capable of handling each requirement on a customized basis, Indexing of data as per requirements and Custom Analytics.

What’s your opinion? Do you see big opportunity for Big Data As A Service (BDaaS) in the marketplace?