DaaS: When Cloud Reins Data

Facilitating access to business-critical data in a controlled manner over the cloud—through Data as a Service—is set to find favor with enterprises

By KTP Radhika

Cloud computing has offered the enterprise world with a handful of services. Among them, Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS) are the most popular ones. Taking a cue from this approach, service providers have also started delivering a similar service—Data as a Service or DaaS.

A relatively new cloud concept, DaaS came to the fore as companies felt the dire need of creating large data stores that could be re-used based on their requirements. Accessing and retrieving data from various systems was getting increasingly complex and tedious. DaaS was a reaction to this problem. Basically, DaaS is defined as consolidating, cleaning and managing
a particular enterprise data set, synchronizing it with business processes, applications and analytics, and allowing controlled access to that data. It is a cloud strategy used to facilitate the accessibility of business-critical data in a well-timed, protected and affordable manner.

DaaS depends on the principle that specified useful data can be supplied to users on-demand, irrespective of any organizational or geographical separation between consumers and providers. It provides an opportunity for improving IT efficiency, performance and decision making through centralization of resources. With advancements in technologies like virtualization, data integration, mobile device management and service oriented architecture, enterprise DaaS strategies also have increased drastically in the last few years.

Research firm IDC notes the economics of data movement are tipping the scales towards distributed compute services. Processing data where it is sitting, will be the model going forward for the next generation of platforms. The implementation and execution of a provisioned Big Data as a service (BDaas) solution will leverage platform, networking, storage, and compute services, expects IDC. Thus, we can see a breakthrough in BDaaS offering in 2013, which will leverage all of these assets as well as solve the challenges of how customers will on-board their data.

Data benefits
DaaS brings in quality to data as it can be aggregated in a centralized place, cleaned, enriched and offered it to different systems, applications or users, irrespective of where they are. Rajesh Ramaswamy, Head – Data Warehousing, Business Intelligence and Analytics Practice, Marlabs Software says, “The biggest benefits of DaaS are in data quality, integrity and standardization as well as in ease of access and processing. It also provides ease of administration, maintenance and collaboration, all of which help in cost reduction.”

Business in these days moves at a very high speed. However, enterprises might not have the resources to fully manage the technical aspects of their data investment. Here, a DaaS interface will help non-expert users to make minor structural changes to data or reports and easily meet their business requirements. It also helps the enterprises in cost saving, since they do not want to invest in infrastructure or data management team.

DaaS not only enables real-time business intelligence (BI), but also helps in high-performance scalable transaction processing. Another benefit is that, it helps to find the total market size and the position in the market with respect to a brand or product as against an interpretation for the micro markets. This helps in providing a macro level layout for the products and services being dealt with by providing an accurate referable data content.

P Sridhar Reddy, CMD, Ctrl S opines, “The benefits for the DaaS customers is the ability to test their empirical business equations against the market data available while the erstwhile process was creating extrapolations on the small sampling database, which was error prone as could be seen from the election result prediction process.” This provides a base on information assurance framework for marketing, sales and after sales processes.

Also, the pay-as-you-go model in DaaS disposes the need to maintain such large data stores by individual corporations and create a large overhead in terms of investment and complexity.
It also brings in agility since customers can move quickly due to the consolidation of data access. If a user require a slight variant of data structure or has location based requirements, the implementation is easy because the changes are minimal.

Sreeharsha Subanna, Vice President – Managed Services, AGC Networks says, “The emergence of DaaS made data attractive and interesting to adopt because it allows for the separation of data cost and usage from that of a specific software or platform. Organizations have used data stored in their storage repository, for which software was developed to access and present the data in a user accessible formats. This led to merging of both the data and the software needed to interpret it into one package, marketed as a single product.”

Current scenario
The DaaS market is in its early stages in India. However, it has a strong growth prospectus. DaaS market is expected to grow as cloud computing and big data are growing and heading towards convergence. The ultimate converge point of cloud computing and big data would be DaaS. A research report by EMC predicts that by 2015 the BDaaS market will reach $2.55 billion and by 2021 it will touch $30 billion. In other words roughly 4% of all IT spending will go into BDaaS by 2012.

Reddy explains, “The current scenario of DaaS market in India is in an early adoption stage. That said, it is picking up quite fast. For instance, the Govt. of India initiatives such as UIDAI or National Intelligence Grid (NATGRID) or census projects, are working on central DaaS services which are being increasingly used by the various other departments and ministries to increase the efficiency of the programs run by them and at the same time leading to lowering the overheads.” The BFSI community has already adopted the DaaS by creating data marts such as those maintained by CIBIL, for the purpose of score-based risk assessment for parking their investments or raising the debt instruments at individual or corporate level.

The industry verticals (for example, retail, banking, market research firms) who have large data to manage and maintain are looking at DaaS options. Ramaswamy points out, “ We see three broad types of organizations using DaaS – organizations with master data challenges (especially customer data integration), organizations with a multitude of enterprise application integration (EAI) type middle-ware systems and those with requirement to access a lot of public data We also anticipate an increasing uptake of DaaS in the Indian market over the next three years once the data collection and dissemination processes are streamlined..”

Different type of pricing models exist to support DaaS platform offerings for both private and commercially available data. These models are relevant whether a firm is a consumer of DaaS or one who provides data to others through a service. Prashant Gupta – Head of Solutions, India, Verizon Enterprise Solutions elaborates, “Tiered access to data appears to be a popular component for DaaS pricing models. The tiers fall in to two major categories, that is, volume-based pricing and data type model.” In the volume-based pricing model you will get two options of paying. One is quantity based paying, where the service provider will charge on the basis of amount of data that the client is accessing through API. And it is the easiest pricing model to implement. Other is pay per call (A “call” is a single response interaction with the API for data.), which is appropriate for lower volume use.

The data type pricing model features tiers essentially based on the number of fields returned in a query. Some more complex pricing models also combine both data type and volume-based features. It depends on the complexity of the underlying data model as well as the level of demand for the data itself. The most complex pricing models combine value with volume charges to create finer-grained pricing to better meet both the buyers’ and sellers’ needs.

Data blocks
Like any other as a service option, one of the main challenge with DaaS is where to begin the same? Subanna explains, “Migration from legacy platform to the DaaS platform is a pain since there has been a legacy framework which has been hosting and managing the data of large size and history. Of course DaaS makes management, maintenance and accessibility to integration seamless, simpler and attractive but the risk is how to migrate and where to start?”

An organization has to survey its applications and data sources and identify those that can be decoupled and those that cannot. The level of effort required to decouple data must also be weighed against the estimated value of doing it. Another pain point is the high fragmentation of the data and loss of collaboration platforms at the macro levels of the verticals. “Such an environment will enable the competitors in a vertical to collate and increase the market size. The harnessing of data by the analytics platforms for providing the services on the DaaS platform is also currently not matured,” says Reddy.

Data security and increasing deprecated regulations are some other challenges the market faces now.

When a company decides to share data to other applications and services or outside departmental walls, privacy becomes a big concern. For instance, handing out healthcare data for secondary use, for insurance providers can invoke privacy concerns of patients.

The other challenge relevant in the BDaaS world is the fundamental challenge of the cloud architecture choking network bandwidth when huge volumes are moving over the network.

Future data pool
Even if there are lots if initial hiccups, cost reduction and complexity reduction that DaaS promises will definitely make it a compulsion for enterprises to look at it in a larger way. It would begin as small use cases and then legacy migration would be over a period of time. Industry experts opine that in future, we can see DaaS being bundled with BI and analytics and comes in as a package. “Instead of providing plan vanilla DaaS offering we will see analytical insights being provided as a value added service,” affirms Ramaswamy . Advances in cloud based encryption technologies will also address security concerns in future.

Businesses across verticals have begun to see their data not only as valuable, but economically viable to share. Seeing the bright prospectus, vendors have started investing heavily in this space. “CtrlS is currently investing heavily in its innovation engines to bring across the offering with mature service,” assures Reddy. This assures that DaaS will be a much sought after space in near future.