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To Scale Big Data You Need Scalable Cloud Qubole Delivers Both

To Scale Big Data You Need Scalable Cloud. Qubole Delivers Both

Qubole's First Event in Malaysia, which took place at Bangsar South earlier today was standing room only as they explained how scalable and flexible cloud infrastructure is the "gold standard" when it comes to a building a big data platform.
 

Qubole's Impressive Customer Base A Full House - Standing Room Only Networking and Knowledge sharing in the breaks

Organisations invest large sums of money in Big Data in order to become data driven and gain valuable business insights that help to drive profit. But, according to Nikunj Vora, Qubole’s Regional Sales Director (SEA & Australia), that is simply not the case for many companies. In fact, he said, “In 2018, Gartner has predicted that 70% of all Big Data projects will fail.” He attributed the failures to three main reasons; Big Data initiatives involve highly complex systems, organisations face difficulty hiring specialised teams, and escalating costs they have to fork out up-front also makes it too costly and risky for companies to, say, “test the waters” or experiment with Big Data. But the cloud allows companies, big and small, to overcome these constraints.
 
“The biggest bottleneck in enterprise-wide adoption is the difficulty of Big Data. Irrespective of the vertical - whether you’re in advertising, healthcare, pharmaceutical or entertainment business, you have an IT team in the organisation, you have a marketing team, you have a business analyst. The same challenges apply to all of them. Big Data is complex for everyone to learn and there are not enough people in the market to hire,” said Nikunj. Since Qubole’s platform makes Big Data automated and seamless, companies can just get started on their Big Data journey with a smaller team overseeing it - therefore reducing the need to hire new people or retrain the existing people.
 
Nikunj spoke in KL today at Qubole’s Big Data networking session titled “Embracing Cloud For Big Data”, where Big Data professionals got the opportunity to meet with data leaders in the industry, and understand some of the challenges and benefits of running their Big Data infrastructure in the cloud. Qubole is a Big Data-as-a-Service company that specialises in helping organisations switch and transition to an autonomous data platform by moving their Big Data workloads to take advantage of the elasticity, flexibility and cost-effectiveness of the cloud. Qubole acknowledges that the data science community in Malaysia is active and thriving, and they intend to be a part of this growing market. In fact, they’re already working with the biggest Malaysian companies that are using Big Data, such as iFlix and Malaysia Airlines.
 
However, that does not at all mean that Big Data is only relevant to large corporations. Nikunj explained, “Big Data is not necessarily tied to big enterprises. For SMEs, Big Data is relevant when they’re dealing with new data sources. A lot of startups and SMEs are creating innovations that don’t deal with historical data sources. For example, when GrabTaxi first started, they were dealing with GPS logs, something that was never done before and they had to move to Big Data technology in order to be successful. So irrespective of the size of the company, I think in some way and shape, if you’re dealing with new data sources and new innovations, you will have to use Big Data.”
 
To address the SME market and drive innovation, Qubole has come up with the Qubole Data Service (QDS) Business Edition which is made available to SMEs at no cost. “The idea behind this is we want to remove that bottleneck to Big Data adoption. We don’t want small businesses to think that Big Data is tough and expensive. We want all SMEs to innovate. We want them to look at new data sources. And we are providing them with an automated platform at no cost so that they can start their journey,” he said.
 
The purpose of today’s event was not only to position Qubole, rather, it was about helping organisations realise the importance of really understanding the cloud infrastructure and how they could implement a Big Data system on top of it; and to highlight the fact that becoming data driven is no longer an option for companies that hope to not only strive, but survive in this data rich world.
 
On this, Andrew Martin, Board Member at AOPG and Vice President of APJ at Zerto, who also spoke at the event, said the following. “The driver for Big Data is really about transforming business and improving customer experience. But the problem is that the people responsible for that have very little idea about what Big Data is, how to implement Big Data projects, and the demands that are involved. So there’s a big challenge that countries like Malaysia are really trying to solve right now, which is how do you get every business to embrace taking on and bringing in the investment for Big Data and data driven initiatives. It’s very, very difficult.”
 
Andrew believes that the solution has to come from two sides. Firstly, executives within organisations need to acknowledge that they have to invest in Big Data, and at the same time, the IT and data analysis side of the business needs to be able to educate the people in the board room about the importance of data driven decisions, and also how they go about doing it. The reality today is that no matter how big a company gets, you just cannot predict if their business model will remain relevant or if they’ll simply disappear due to the power of data.
 
Andrew acknowledged that whilst Zerto is not a Big Data company, their resiliency platform is helping companies embark on their transformation journeys. One area where that is seen in practice is enabling companies to move their applications to and between public clouds, with both Andrew and Nikunj stressing that cloud infrastructure is a critical element of Big Data and business transformation. This brought the discussion full circle with Nikunj explaining that understanding cloud is complex and costly. Qubole’s autonomous data platform looks after driving cloud efficiencies so that data experts can focus on data, not infrastructure.
 
 

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