In The concept of cloud is no longer relegated to non-critical applications, but is actually extending to business intelligence and analytics, thus pushing it to a new level. So far, the industry has witnessed large enterprises harnessing the power of cloud based BI and analytics model. But now, mid-sized and smaller companies are gearing up; so much so that the BFSI segment is leveraging it to a great extent. In other words, a cloud based BI and analytics strategy is creating a level playing field across small enterprises.
One key reason for this, as most BI and analytics vendors and users agree, is that cloud-based services can support a huge amount of data; and it is one easy and cost effective way to deploy BI and analytics solutions, thus giving it that competitive edge. Most industry players echo the opinion that cloud Based BI is particularly important to SMBs who are primarily leveraging the public cloud, as most of the large enterprises are opting for hybrid models.
Rajesh Shewani, Technical Sales Head, Business Analytics, IBM India/SA observes that disruptive business models, enabled by analytic and cloud technologies, will change the game of corporate sales and supply chain operations quite similar to the way the book, Moneyball tells how professional athletes changed baseball by leveling the playing field with cash-rich teams through the innovative use of analytic.
Shewani affirms that IT teams are mapping their data using cloud based BI and analytics and using the tools effectively. Customers are using both our BI and analytics tools across various pre-defined scenarios spread across account receivables, various other transactions, production etc., says Shewani.
How does cloud BI & Analytics Map your Data?
While the term cloud can mean different things to different people, IBMs Shewani says cloud services typically require technologies and approaches such as standardisation, virtualisation and automation, and they typically consist of the following characteristics:
On demand self-service
Broad network access
Shared resource pools
Rapid elasticitydynamically assigned resources
Measured servicepay as you go
According to him, organisations are using the power of cloud to build enduring customer relationships, deliver IT without boundaries, improve speed and dexterity and transform the economics of innovation; and cloud analytics refers to applications that use cloud resources for analytics processing or the delivery of analytical insights. Shewani goes on to say that customers are increasingly using cloud based analytics and BI to reassess outdated strategies and identify new ways to improve efficiency at a lower cost.
As part of our strategy to deploy private cloud computing environment for business analytics, we launched an internal project to standardise BI across departmentsnot only to better understand key business objectives and deliver leading solutions and services to clients, but also to maintain budget and, where possible, uncover new savings, says Shewani.
An enterprise, which leveraged cloud BI & Analytics
Elaborating on a case, he said a large enterprise from an IT vertical needed a centralised business intelligence solution that was highly scalable for a distributed workforce, available to more users, provided ease-of-use and allowed the organisation to execute its BI strategy.
The solution Blue Insight was deployed; it provided always-on access to the right information at the right time for smarter business decision-making, while enabling the company to cut down on infrastructure cost and complexity, and reduce siloed data and duplication of efforts.
The key benefits, according to Shewani, was a 70 per cent decrease in cost for BI delivery, standardisation on a centralised, scalable infrastructure, consolidation of many multi-product, departmental BI deployments, and access to information from nearly 100 different data sources for real-time decision-making .
Vendors like Ramandeep Singh, CEO, Alten Calsoft Labs, argues that the unprecedented data growth offers opportunities as well as challenges for enterprises. According to him, cloud based data inference provides enterprises an opportunity to analyse structured and unstructured data and take strategic action.
CIOs and IT Decision Makers see the use of Business Intelligence (BI) in the cloud as a game-changer, as it makes BI affordable and easily available as compared to traditional BI, says Singh
Cloud based BI and Analytics solutions offer several advantages over traditional BI implementation in terms of cost benefits, flexibility of implementation, availability and speed of implementation, he adds.
Singh points out that BI/DW applications demand high infrastructure requirements, handle unpredictable load volumes, involve high upfront investment, high development and maintenance costs, take a longer duration for provisioning and have so far displayed a high reliance on IT. On the other hand, cloud based BI can be adopted faster with low initial investment on infrastructure and overhead costs, which is why it can be leveraged by medium businesses and those who have not tried out on-premise solutions.
Sandeep Bhagat, Principal Architect, Big data & Analytics, Infosys, strongly believes that technologies that are among the fastest adoption in cloud are BI and Analytics. According to Bhagat, in late 2011, only about 13 per cent of enterprises worldwide had cloud-based BI solutions. In 2012, cloud-based BI saw an 84 per cent CAGR.
On a more positive note, Archana S Awasthi, Vice President & Head- BFSI, Ramco Systems, says cloud based BI and Analytics is no longer a novice as most customers in the BFSI segment are leveraging the model under the public cloud. Customers are looking at a data centric BI cloud model; we have brought in standardisation in the cloud based model, while creating industry templates, says Awasthi.
Awasthi says that traditional analytics solutions are built ground-up, are very complex and take many man-months to implement. The vendor has leveraged its existing ERP customers to deploy OnDemandAnalytics and Gateway products on the Cloud, which comprises a comprehensive BI platform to address large, scale enterprise data warehousing requirements.
Awasthi observes that the cloud model would enable customers to quickly and easily adopt business applications and then graduate to a full-fledged ERP, without replacing the existing system. Gateway products offer a fusion of transaction and decision support systems (i.e. ERP with self-contained Analytics), thereby supporting both operations and decision-making.
This will ensure that customers, who hitherto could not afford an Analytics offering, can start using the solution easily, she says.
What IT Heads foretell
IT Heads agree with vendors on the cloud based BI and analytics throwing up equal opportunity to small, medium businesses who are constrained by the cost.
To this effect, T G Dhandapani, CIO, TVS Motors, explains that BI and Analytics being strategic initiatives, this tool is housed on private cloud. There are three different BI and analytics platforms: two for BI, of which one is open source. The third platform is for doing data mining. BI is centrally developed and offered in the private cloud model as shared services for the group, says Dhandapani.
Lets take a look at the areas of investment that BI and analytics solutions draw. In any given scenario, as Dhandapani observes, If we take the life span of the tool to be at least 8 years, the major cost is the cost of the data Scientist who works on the tool to get major insights. The initial investment in licensing, servers, storage and AMC constitute around 40% of the total cost spend in a span of 8 years. As for the initial investment, the cost of implementation is significant followed by licensing and storage.
Against this backdrop, the cloud model does seem to be a viable proposition.
Kaushal Shah, Head-IT of Privy Organics, who has plans to deploy BI and analytics solutions in the near future, intends to try the cloud-based model for the delivery management solution, to begin with. Every organisation has its unique model around planning management, capacity management, availability and operations and delivery management. While there are challenges to adopting a cloud model for most functions, I would definitely look at delivery management functionality on the cloud model for BI and analytics which would allow me to execute faster transactions and meet compliance needs, avers Shah.
Shah agrees that this model would help enterprises in creating a level playing field by bringing in sustainability and efficiency into the system.
Vijay Sethi, CIO of Hero MotoCorp recommends that IT managers initiate cloud BA project with a pilot; the objective being not to test technology but to ensure that the team and users get comfortable with analytics. However, the success of a BA project does not depend only on technology there are other factors: people (users), processes (of data collation, extraction, review etc) and the culture of the organisation. Based on learnings of the pilot, rollouts should be undertaken, says Sethi.
From the preparation perspective, the CIO has to first convince himself that as far as implementation of any analytical tool is concerned, it needs to be taken up as a journey instead of project because:
As capabilities are demonstrated, the demand for information increases.
The rules of aggregation generally tend to undergo an evolution over a period of time: initially managers have a tendency to ask for transactional information, but with time, it moves from reporting to intelligence to analytics (both IT and users undergo an evolution).
Considerable change management effort required to make users use these kinds of systems in most cases, they are more comfortable with their excel sheets and pivot tables
Accuracy of data increases with time as the usage increases and then the demand for analysis increases
Add new comment