Monday, 3 October 2016

Common myths and truths about BDaaS

software outsourcing companies

It’s exciting to see Big Data-as-a-Service (BDaaS) starting to take off. Numerous media outlets have covered the effect of this emerging trend on software outsourcing companies. While there is not yet a precise definition of BDaaS, common subjects are emerging and diverging. Here is a take on some of the truths on BDaaS:

All of the BDaaS service providers have slightly different capabilities

A host of services now uses the BDaaS signature. These services have both commonalities and key differences:

Most vendors are cloud-based, but with different architectures such as single-tenant and multi-tenant. These BDaaS vendors are promoted as a managed service with varying levels of management. Some are Hadoop based or other open-source software based. A few vendors include access to external or third-party datasets. A few have their own innovative visualization capabilities, but most of them support industry-standard tools.

Most BDaaS vendors essentially offer Big Data Analytics Processing-as-a-Service. This distinctive issue will persist, requiring that buyers be assiduous in their evaluations.

Currently, as a consequence of the Big Data trend, enterprises can turn to Big Data as a Service (BDaaS) solutions to bring the storage and processing together. Interestingly, a definition and classification of BDaaS is missing today and various types of services compete in the space with varied business models and foci.

Big Data-as-a-Service improves enterprise dexterity and competencies

With big data’s well-documented capability, an outsider might wonder why most software outsourcing companies don’t have programs to implement BDaaS yet. There are a lot of complex new technologies, legacy investments, many other IT priorities and a shortage of skills that is delaying this implementation. BDaaS removes many of these technical and skill blockades to data processing, so enterprises can focus on using data efficiently and be more flexible and adjustable to change. BDaaS enables smoothness, agility and compatibility. For instance, enterprises find it's relatively faster and easier to adapting changes at lower cost and efforts. Smoothness is the extent to which your BDaaS can be quickly and cost-effectively repurposed and reconfigured in response to changes in the constantly moving world.

Security, privacy and integration are key issues for BDaaS

While many software outsourcing companies in India have developed skills and competencies to manage these worrying data challenges on-premises, the cloud is an altogether different environment. Organizations still find it difficult to understand this new paradigm, and integrate it with substantial legacy investments. BDaaS providers, many of which are digital groups and software companies, often have different approaches on issues like security and integration, requiring careful inspection.

Implementation challenges can arise from lack of preparation, crisis in expertise and compromised data security, all of which will have to be taken care of in the future management of BDaaS technology.

Here are some common myths on BDaaS:

Hadoop as a Service = Big Data as a Service

Big data is not only about Hadoop. While earlier definitions often closelycharacterized big data as newer formats like semi-structured data (sensor data,logs etc.), in common use, big data is often used for “all the kinds of data a company has to deal with.” (TechTarget, 2016)survey provides a meaningful insights on format of database organizations consider “big data”:

79% include structured i.e. organized data (e.g. customer records and transactions)
59% include semi-structured i.e. semi organized data (log, clickstream,sensor, social)
52% include unstructured i.e. unorganized data (videos, audio, images)

Add to this there are lot of analytic processing requirements for different data jobs in a company(real-time, batch and advanced), and clearly Hadoop is not the suitable engine for every big data job. That’s why visionary BDaaS providers offer multiple processing engines (Hadoop, MPP SQL and Spark) to address the full range of data and analytical needs.

Big Data-as-a-Service threatens Information Technology

BDaaS is poised to help IT leaders and enterprises, empowering them to quickly offer big data capabilities within the scope of existing data and governance programs. Instead of stickingto Hadoop for six months, IT can source BDaaS that meets companywide requirements and then reallocate crucial resources to help the business analyze data more effectively. IT can rapidly implement BDaaS in days or weeks, enabling their organization with extraordinary data access, infinite scale and new agile data analytics capabilities.


The term ‘Big Data as a Service’ may be rather inelegant and clumsy but the concept is not. As more and more software outsourcing companies in India realize the value of implementing Big Data strategies, more services will emerge to support them as well. Data analysis brings positive change to any organization that takes it earnestly, and this includes smaller or larger scale operations which neither have the expertise nor the budget nor time to develop that expertise to do it themselves.


TechTarget. (2016). TechTarget Big Data Analytics .

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