GEC NEWS WIRE“With all the disruption happening within the big data market, it is indeed clear that it is an intimidating task to select amongst the vast array of tools and technologies within the big data landscape.”
Ali Rebaie, Industry Analyst and Consultant Big Data
Why do you think it is important for there to be a dedicated Big Data and analytics event in the Middle East?
If we follow the timeline of international big data events since 2010, we can see how these events are setting the industry trends each year and showing the latest innovations from big data start-ups.
I was one of the first to speak about Big Data in the Middle East back in 2013. I have witnessed how things have evolved since then and being present in most of the important big data events has allowed me to see how the region is evolving when it comes to embracing big data. In parallel, the responsibility of mentoring one of the first data science teams in the Middle East region, enabled me to experience the real challenges faced by any big data start-up from distinct perspectives.
How important are events such as The Big Data Show to sharing knowledge and information within the big data and analytics industry?
What’s unique about the Big Data show is that it brings the experience of its organizers in exhibitions, in addition to this, the panels, fireside chats and keynotes which in term not only present the latest trends to the Middle Eastern audience but also show the latest innovations from start-ups in our region.
What potential impact could the adoption of big data strategies have on Middle Eastern industries?
With all the disruption happening within the big data market, it is indeed clear that it is an intimidating task to select amongst the vast array of tools and technologies within the big data landscape. In addition, organizations cannot jump to implementing a Hadoop cluster for example before assessing their maturity as an organization when it comes to their people skills, processes, and technology infrastructure. Big data strategies need to be set up in organizations from distinct industries before implementing, and we have been witnessing the need for such strategies in order to set a roadmap which can then enable them to get buy-ins for their big data projects in a timely manner.
Can you identify some of the greatest technical challenges facing organisations which are looking to adopt a big data strategy?
Technology challenges like data silos, traditional data governance methodologies, and data integration are core whenever organizations think about adopting big data strategies. However, in my point of view, culture is a more important challenge as organizations realise the potential rewards and value they can get out of big data. Our experience with different industries in the region like the Oil & Gas, transportation, media, marketing, and retail industries are all beginning to realise this and are moving to a more data-driven approach, which is the key factor to being on the competitive edge in a big data era.
What are the current big data analytics technical solutions available to companies to overcome these challenges?
Part of our work with big data vendors and start-ups, we have seen innovative solutions in data preparation which are packaged as business user-centric products which then enable automatic and algorithmic-based data cleaning and preparation. Thus, filling in the gap of both data integration and the need to collaborate with business users within a data-driven environment. Also, other innovative approaches to data integration is starting to get a spark in the market, such as data virtualization which can solve different challenges for organizations who are reluctant in investing in data due to data privacy and sharing restrictions.
What upcoming analytical innovations do you feel will be able to solve the current big data limitations in the market?
The analytical capabilities within the big data market are maturing. Connection Analytics is one of the most promising method which I think it will revolutionize the way we look at data in different industries.
Beyond delivering customer insights, in which areas of business can big data improve operational efficiencies and strategies?
To me, big data is affecting all industries and even all areas in our life on earth, there will be no area untapped by the big data era. Beyond customer insights, enterprises can become resilient by using big data. Oil & Gas companies can use big data for predictive maintenance, banks can use the new analytics capabilities to predict fraud, telecoms can improve their network infrastructures, insurance companies can reduce the number of potential losses and costs from claims processing and collection recovery situations.
How new technology is affecting worldwide big data strategy and influencing modern business models, in respect to the Middle East and within the wider market in general.
Since 1965, organizations wanted to gain insights from data by the use of expert systems and artificial intelligence, however, it did not work as we aimed at that time. We just didn’t have enough computer processing & analytics power at the right price to accomplish those ambitious goals. Today, with the technology available to us and with “ephemeralization of Big Data”, we are capable of achieving much more.
*Ephemeralization of big data is a recent concept I talked about in an article in wired magazine.
What are the most important recent developments in big data and analytics that you believe will have the biggest impact on the industry? What developments should the market be aware of that they aren’t already?
In 2015, a new technology called “Spark” is getting a lot of attention. The market is already aware of MapReduce “batch” processing through Hadoop. Spark, a project born at Berkeley University before being available to the industry, is now enabling real-time data processing and engines for streaming and machine learning, all of which was not possible through batch processing with MapReduce previously.
Can you give a basic outline of the relationship between structured and unstructured data, and how that may create challenges for companies across the Middle East?
I would like to take the opportunity to demise the myth that says we are replacing all our current traditional BI & Data Warehousing technologies with big data technologies. The suitable term to use in this context is “augmentation”. We are augmenting with these technologies that are well suited for started data with new big data technologies that are more suited for unstructured data. If we think of it in this “unified-extended” view, we could solve a lot of our challenges.
