What companies want are real, tangible results from any Big Data project. Yes, I understand I am stating the obvious. Yet judging from the many Big Data solutions entering the market today, it’s not clear that everyone does. So many vendors seem to equate Big Data with Data Warehousing 2.0 + Data Mining. But that falls short.
For any Big Data project to deliver real results it needs to:
- Align to business priorities,
- Integrate with business processes, and
- Operate at the pace of business
Any approach that doesn’t meet these three requirements is just “Big” or just “Data” – neither of which is particularly interesting on its own.
Linking the business imperative to all your data, across all stakeholders with implicit contextual value, is the only real way customers will be able to monetize the Big Data investments. If customers are observing business misalignment, they should consider “re-booting” the project immediately or suffer the consequences of sub-optimal results.
Unfortunately, many companies start by collecting data (and lots of it), budgets get depleted and then in an attempt to justify the costs they try to more directly link it to a business problem. It’s like pushing water uphill. Instead, go with the flow and make the business priority the starting point.
The best way to get started in the right direction is to engage data scientists who know your industry, and can make the link between your business, your data, and your IT.
The organizations that achieve the greatest results tie Big Data insights directly into their business processes and their people, allowing them to act upon insights in day-to-day operations. Understanding Business Processes should be the next conversation, right after you understand the Business Priorities.
You want to be thinking about how to “Big Data enable” your business processes and enterprise applications, and how to equip your frontline workers with the insights they need. Understanding this will be critical to building robust Big Data architecture that delivers results.
Look for a comprehensive data platform and integrated analytics suite foundation that address all of your stakeholders and Big Data application use cases, and that can seamlessly interoperate with existing and new business processes. Any Big Data vendor who only talks about data warehousing or data mining is falling far short of where you need to be.
In the context of business priorities and business processes, it becomes clear that the real IT challenge is to acquire, analyze and act on Big Data insights at the pace of business.
Employing conventional wisdom, traditional databases can indeed store petabytes of data. The problem is that when you start dealing with the expanding footprint of unstructured data and relying upon these traditional environments the conventional RDBMS system cannot keep up – in fact, it grinds to a halt! Switching on a traditional database’s in-memory feature may get the gears temporarily moving again, but it’s a duct tape solution that won’t last when data grows to the next level of complexity.
To keep pace with business Big Data architectures need to deliver instant results from infinite storage. That requires a truly in-memory platform like SAP HANA connected to massively scalable data storage like Hadoop.
Sorry but Big Data focused on analytics and data warehousing alone isn’t enough. It’s nothing personal. It’s just business; and its priorities, processes, and pace!