Discovering Big Data in Malaysia

Big Data is a growing interest to a lot of companies and government organizations worldwide. Market researcher IDC predicts spending on Big Data technology and services to grow at a 27% compound annual growth rate (CAGR) to US$32.4 billion through 2017. Closer to home IDC estimated that Malaysia may have spent as much as US$18 million on Big Data technology in 2013, and predicts this figure to rise to US$24.2 million in 2014. The researcher cautions though that organizations need to adopt a strategic approach to Big Data adoption as opposed to being siloed as is currently commonly seen.

This was echoed by Ms Queenie Wong, Practice Lead, Information Management at SAS Malaysia, recently spoke to DataStorageAsean to talk about the Big Data opportunity in Malaysia.

DSA: What does Big Data mean to SAS?

Queenie Wong: Big Data is data that comes in big volume, high velocity and high variety. It comes both in structured format, as in machine generated data like ATM transactions or event triggers generated in a manufacturing production floor. It also comes in unstructured format as in the case of data derived from crawling the web for information or social media chatter.

DSA: Is Big Data just for Big Customers?

Queenie Wong: In a word no. Big Data has transformed the way companies look at data, data management and analytics. Companies that previously could not comprehend Big Data are now looking at managing this repository of data because of the opportunity available through new technologies to better access, manage and analyse the Big Data.

Previously companies were restricted by cost and the channels they go to market. This meant only large organizations had the resources to build systems and processes to capture and potentially mine this large information store.  Today organizations, for example like telcos, can look at data derived from sources like call detail record (CDR), not only from a billing point of view, but also to understand customer trends and behaviour. Because of current technologies and storage, they are able to better manage these sources of customer, hence harvesting the value of Big Data.

Because of its volume, velocity and variety, organizations need to understand the value they could derived from Big Data. Just because you have 20 TB of data sitting in your storage doesn't mean you need to comprehend all of it. You need to understand the key values that this Big Data bring to you – this would allow to analyse it better. The key to big data is to understand the value that you can harvest from this big data repository.

DSA: Is the hype of Big Data helping or hindering the SAS business?

Different organizations, including analysts and vendors, look at big data differently. Some look at it from storage, others in terms of the capacity to capture and store. SAS looks at big data from a value point of view. If you ask me if it’s hyped... definitely everybody is excited because finally you can buy storage very cheaply, but to SAS the key thing is how to manage and comprehend this big data so that it gives you value. For example in a manufacturing environment where data is created at all points in the manufacturing process, companies will want to know how we can use this big data to help shape the quality of final product – things like reduce product failures or even managing the machines from a maintenance point of view. So SAS looks at Big Data in terms of how do we help the customer comprehend this Big Data so they can derive more value from this Big Data?

DSA: How does SAS work with other technologies for example Hadoop?

Queenie Wong: We are very big in Hadoop. We are more than the word “support”. SAS is very into Hadoop in the sense that we process our analytics capability in Hadoop. Our solution resides in Hadoop to give the customer faster, more flexible and more scalable capability. We don't just query or store in Hadoop, we run our logic and analytic computation in Hadoop itself.

DSA: How has things changed for SAS with the arrival of Big Data?

Queenie Wong: SAS has been in analytics for the last 38 years Big Data is not new to us. We do analytical work for banks and telcos to understand how they could comprehend their customer data. New technologies and the rising popularity of Big Data mean that we have more customers asking us to help them comprehend what the Big Data means to their business.

DSA: What is the profile of the SAS customer?

Queenie Wong: We have big global customers, like telcos, manufacturers, banks and government, right down to SME. SAS solution is available on an enterprise-scale, on departmental scale, and also on desktop scale. For any customer that wants some analytical capability – the question is how large is your deployment? For example, we do simple analytic capability such as financial forecasting. SAS serve customers who want to understand their data better and they have some form of electronic capturing of data. We focus on customers that recognize they have a challenge in understanding their data and they want to have better business insights.

DSA: How do you see Big Data in Malaysia?

Queenie Wong: Big Data is getting a bigger presence in Malaysia. A lot of banks, government and even manufacturers understand and are leveraging to store this information. We have a couple of implementations in Malaysia that dealing with customers with big data where our analytical capabilities are sitting on Hadoop for example, and Hadoop is a source for them to capture data. I would see more customers going into this space as the business gets global. Everyone is in the ecommerce capacity - these are the kind of drivers that would increase customer awareness and adoption in knowing more about using analytics to understand the big data that they have.

DSA: For any customer that wants to deploy an analytics solution, do they need to have a large infrastructure in place?

Queenie Wong: Not necessarily. They can leverage the cloud capability from providers like Amazon. Some of our customers do not want to invest in the hardware infrastructure because their core business is something else, so they want to subscribe to what's available out there in the most opportune cost. A lot of customers are looking at this because of its ability to scale. Today (through the cloud) companies can have sophisticated infrastructure through a subscription model.  And we support that. In Malaysia there are customers that prefer to use managed services on and off premise, cloud-capability. It very much depends on the customers’ business directions – in terms of how they want to invest in technology. I do see it’s big and rising. Many of our big Asian customers are also on a managed service environment. That is leveraging on best of breed capabilities to do what you need to do to get going.

To know more about Big Data, watch this video.

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