Skip to main content

(Guest Post) Value And Insights: Yves Mulkers ahead of Big Data World 2017

 John Bensalhia talks to Yves Mulkers, freelance Data Architect and blogger at 7wData, about the benefits, developments and challenges linked with Big Data...


“I'm an explorer on new technologies and Data Visualisation, and keep my finger on what's happening with Big Data from an architecture point of view.”

So says Yves Mulkers, freelance Data Architect and social media influencer. Yves is speaking ahead of upcoming Big Data World event in London, where he will make an appearance. Listing the key benefits of what Big Data can offer, Yves says that these are:

“Scalability, cost reduction, new products and revenue streams, tailored solutions and targeting, enterprise wide insights, and Smart cities.”

Having worked as a software developer in various branches, Yves achieved great expertise and mindset in object oriented thinking and development.
“Doing the full cycle of software development from analysis, implementation, support and project management in combination with a strong empathy, he positioned himself as a technical expert bridging and listening into the needs of the business and end-users.” 

Yves says that this past year has seen a number of breakthroughs in the development of Big Data such as:
“Integrated platforms, data preparation automation, automating automation, GPU and in-memory databases, Artificial Intelligence, micro services, IoT (Internet Of Things), and self-service analytics.”

Big Data can be used to create a competitive advantage in various ways for businesses. In addition to a 360% Customer View and narrower segmentation of customers, Yves says that next generation products, real-time customization, and business models based on data products are the new approaches. In addition, better informed decisions, such as the measurement of consumer sentiment are good gauges of raising the value of what Big Data can bring.

Businesses must consider a variety of aspects in order to ensure successful Data implementation. Yves says that businesses must have clear business processes and information state diagrams, and should also ensure that they are on top of their game with respect to training and documentation. Data standards must also be developed and complied with.

For applying data analytics and applications in a business, Yves explains that there are challenges to tackle:
“Creating value from your data products, finding the right talent and tools, maturity of the organisation in information management, and trusting the results of analytics. It's worth noting that Big Data and analytics are not the same as business intelligence.”

In the next five to 10 years, Yves says that:
“Big Data will become the business intelligence of now.”

In addition to businesses and companies, aspects of Big Data will be for everyone to take advantage of:
 “Big Data will be embedded in companies strategy, and analytics will become available to everyone. “
“Data volumes will keep on growing as data products will become a commodity and improve our quality of life.”

Looking ahead to the event, Yves says that he expects it to bring a lot of value and insights.
“The combination with the sidetracks around Cloud and others, will bring a broader view on the complete architecture (business, technical and data) needed to be successful in Big Data implementations.”

Comments

Post a Comment

Popular posts from this blog

Machine Learning and Cognitive Systems, Part 2: Big Data Analytics

In the first part of this series, I described a bit of what machine learning is and its potential to become a mainstream technology in the industry of enterprise software, and serve as the basis for many other advances in the incorporation of other technologies related to artificial intelligence and cognitive computing. I also mentioned briefly how machine language is becoming increasingly important for many companies in the business intelligence and analytics industry. In this post I will discuss further the importance that machine learning already has and can have in the analytics ecosystem, especially from a Big Data perspective. Machine learning in the context of BI and Big Data analytics Just as in the lab, and other areas, one of the reasons why machine learning became extremely important and useful in enterprise software is its potential to deal not just with huge amounts of data and extract knowledge from it—which can somehow be addressed with disciplines such as data

The BBBT Sessions: HortonWorks, Big Data and the Data Lake

Some of the perks of being an analyst are the opportunities to meet with vendors and hear about their offerings, their insight on the industry and best of all, to be part of great discussions and learn from those that are the players in the industry. For some time now, I have had the privilege of being a member of the Boulder BI Brain Trust (BBBT), an amazing group consisting of Business Intelligence and Data Management analysts, consultants and practitioners covering various specific and general topics in the area. Almost every week, the BBBT engages a software provider to give us a briefing of their software solution. Aside from being a great occasion to learn about a solution, the session is also a tremendous source for discussion.  I will be commenting on these sessions here (in no particular order), providing information about the vendor presenting, giving my personal view, and highlighting any other discussion that might arise during the session. I would like to start with

SAP Data Hub and the Rise of a New Generation of Analytics Solutions

“Companies are looking for a unified and open approach to help them accelerate and expand the flow of data across their data landscapes for all users. SAP Data Hub bridges the gap between Big Data and enterprise data, enabling companies to build applications that extract value from data across the organization, no matter if it lies in the cloud or on premise, in a data lake or the enterprise data warehouse, or in an SAP or non-SAP system.” This is part of what Bernd Leukert, SAP’s member of the executive board for products & innovation mentioned during SAP’s Big Data Event held at the SAP Hudson Yards office in New York City as part of the new SAP Data Hub announcement and one that, in my view, marked the beginning of a small yet important trend within analytics consisting on the launch or renewed and integrated software platforms for analytics, BI and data science. This movement, marked by other important announcements including Teradata’s New Analytics Platform as well