Taking a look at the Big Data frenzy one should ask the question, how much of Big Data is actually useful.
By applying just a little common sense, we discover that it’s only a small amount.
We have been working with data for over 40 years, and if we go back to pre-internet days we experienced what we called data overload. We discovered then that data itself wasn’t valuable, but only a small slice of that data proved to have a direct impact on actual business decisions. With history in mind, what has really changed in solving the most critical issue is related to finding the data that is actually useful. Well, volume has certainly increased, but what is important to deal with is that much of the growth in volume comes in the form of unstructured data. So we will start with “What is unstructured data?” using the definition from Webopedia.
Data can be designated as unstructured or structured data for classification within an organization. The term unstructured data refers to any data that has no identifiable structure. For example, images, videos, email, documents and text are all considered to be unstructured data within a dataset.
While each individual document may contain its own specific structure or formatting that is based on the software program used to create the data, unstructured data may also be considered “loosely structured data” because the data sources do have a structure but all data within a dataset will not contain the same structure. This is in contrast to a database, for example, which is a common example of structured data.
So looking back in history we are talking about data overload with an added new twist called unstructured data, which represents much of the new volume being generated. We would suggest that companies which bring a combination of strong data analytical expertise along with a good grasp of both industry standards and compliance rules can offer precise filtering solutions that can identify the most valuable data for the user.
Peeling Back the Onion
While there are numerous solutions emerging that address the filtering and analytics of structured data such as Splunk, enterprises collect, index and harness all of the fast-moving machine data generated by applications, servers and devices — physical, virtual and in the cloud.
In the case of what Hadoop brings to the table, there are many others that have debated its pluses and minuses and we will leave that topic to them.
The real challenge is to provide costeffective solutions that address the much more complex world of filtering and real-time analytics of unstructured data. Additionally, extracting value from Big Data requires trained experts who understand semantics, statistics, algorithms and analytics. Currently these resources are hard to find. According to a recent McKinsey study, the U.S. is now facing a shortage of talent with the expertise to understand and make decisions around Big Data.
While the volume of all data types is expected to grow 800% in the next five years, 80% of that growth will be unstructured data. We would suggest that companies which possess skills and capabilities that include data modeling, analytics, OCL and ontology have a leg up when it comes to delivering solutions that leverage both structured and unstructured data. As of today, the jury is still out on who will be the players that will offer compelling solutions that address the holy grail of finding the needle in the haystack in the growing world of Big Data.
One approach to consider
No Magic has a solution that will improve the time it takes to react to ever-changing customer needs, provide keener business intelligence, and lay the foundation to more effectively deal with identifying what part of the Big Data hype might be relevant to your need. One of the key elements needed to ensure you are able to analyze the right customer trends is to have an enterprise-wide platform that integrates all of your legacy systems with your newer cloud and mobile applications. We offer end-to-end integration of your operational legacy systems with your newer customer-facing applications that may reside in the public and private cloud.
The Cameo E2E Bridge
The Cameo E2E Bridge provides any enterprise an easy way to integrate legacy systems with new cloud and mobile applications. This platform uses a 100% business model approach that delivers much greater business transparency than alternative methods. Since the platform is 100% model driven, it lays the foundation to model both structured and unstructured data in the exact format that is most relevant to your specific business need. To top it off, when it is time to implement Hadoop, the Cameo E2E Bridge provides a direct interface, providing for a complete end-to-end solution.