Let’s start with a simple example of what a workflow is. Drawing blood is required in order to diagnose a patient. Simple. In technical words, data workflows are a series of activities (tasks) performed in a reasonable sequence (flow).


What you may not know is that data workflows apply to a wide range (if not all)of industries. Astonishingly, Gartner released a study saying that 60% of Big Data workflow projects fail– a clear statement on why almost everyone feels under pressure to deliver results, now. Thankfully, you are not alone, and as more people try to find solutions, more tools are now available to increase business success.


So how do you ensure your Big Data project does not fail? First, we must understand the reason why one should implement a data workflow. There are four areas within a business that are often trying to innovate with AI, or analytics. Their targets are: 


Profit

Cost

Customer Experience

Risk


Naturally, IT and BI departments will process mountains of raw data in the quest to find correlations, peaks, tendencies, etc which are then used to make their models so they can optimize on these targets. Now, this process happens without the involvement of the people who really understand the business. That’s right: STRATEGY. Without knowing what to look at, it is impossible for data scientists to know what algorithm to run in order to have relevant information to act upon. And this is why data workflows fail.


The solution to this problem, is to collaborate between departments recurrently, so all team members are looking at the data in real-time as a interconnected world.


Unfortunately, we are still in the early stages of innovation. Nick Heudecker, Gartner analysts said that the primary causes of failure are the difficulty inherent in integrating with existing business processes and applications, management resistance, internal politics, lack of skills, and security and governance challenges. Meaning, prior to unifying departments, companies must be open to new ways of work. He went on to say "Organizations...need a plan to get to production. Most don't plan and treat big data as technology retail therapy." This isn't surprising, since big data vendors, from legacy stalwarts to buccaneering startups, all basically promise the same thing: Buy my expensive and hard-to-use technology stack and you'll magically get [insert the buzzphrase of your choice; I like "360 view of the customer"].


Productivity in business success is changing rapidly and radically. It is no longer defined as building more with less. Consequently, value is attached not only to sheer output but to innovation, to be one step ahead and creatively respond to new and evolving market opportunities. Nowadays, competitive advantage is dominated by those companies with flexible operational structures and tools in hand to create new actions and often outperform the time to market of their competition.

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