A new article comments on the complexity of Big Data and the limited view that many companies still have regarding Big Data’s potential. It states, “More than structured information stored neatly in rows and columns, Big Data actually comes in complex, unstructured formats, everything from web sites, social media and email, to videos, presentations, etc. This is a critical distinction, because, in order to extract valuable business intelligence from Big Data, any organization will need to rely on technologies that enable a scalable, accurate, and powerful analysis of these formats.”

It continues, “On this point, the learning curve for most organizations is quite steep. Not only do they have to start considering unstructured information as part of their business intelligence process, but they also have to learn that extracting insight from unstructured data is a much more complex and qualitative process than traditional business intelligence.”

The writer adds, “While I think all enterprises can agree that unstructured information is important, when it comes down to the practical application of Big Data, everyone seems to revert to social media sentiment analysis. Certainly this approach has value in an overall business intelligence strategy, but I believe it’s overrated compared to other areas that can provide more strategic, big picture value.”

Read more here.

 photo credit: Dinohyus Hollandi

A recent article reports, “Intergence Systems, an IT optimisation consultancy firm, has found that companies are often reluctant to migrate to the cloud when there are still on-going security and management concerns around data management. Cloud based services are expanding but are also frequently viewed with suspicion, particularly for reasons such as data governance and security. Intergence Systems believe that visualisation is the first step to creating trust within the cloud; by providing better tools to track resource usage and troubleshoot issues, any company within the cloud can begin to have confidence in their ability to respond to issues as they arise.”

The article continues, “With more resources moving to the cloud, keeping a close eye on the more nebulous parts of the network is becoming difficult for IT managers and CIOs. Visualisation can assist in troubleshooting and checking performance which can prove especially useful in cases where companies suspect a security breach.”

Stace Hipperson, CTO of Real-Status added, “Today’s I.T. infrastructure is complicated and this complexity is increasing. More and more devices are becoming IP enabled, virtualisation and cloud computing have become mainstream, and data rates are exploding… While virtualisation increases ROI, it also increases complexity and makes capacity management even more important. Your business runs on its I.T. infrastructure, so you need to fix issues as soon as they emerge and become proactive with the issues that may arise in the future.”

photo credit: ☺ Lee J Haywood

Russ Hill recently wrote about the data governance troubles facing retail companies. Hill writes, “When managers think about a business, they do so in terms of data: sales volume, inventory, margin, product turn, operational overhead, and other metrics. Data is the language of business. It’s the basis of functional control and, above all, of decision-making. Our ability to figure out where to go next depends almost entirely on our ability to understand where we are now. All other things being equal, then, the better our data, the better our decision-making. Unfortunately, business managers often find themselves in the position of having to make decisions based on data that is inaccurate, incomplete, out of date, or all three together.”

The first retail data problem Hill addresses is complexity: “In retail, many problems stem from the sheer complexity of the data. Retailers deal with customer data, product data, and data from their own internal business processes. And the complexity is further increased by retailers’ drive to define and differentiate themselves from their competition. Business process data is fairly straightforward, but customer and product data tends to be extremely complex. The data on a single inventory item may include SKU, package quantity, size, tie/high, cube, color, weight, price, safety characteristics (e.g. flammability), environmental characteristics (e.g. recyclability), sentiment, and several hundred other attributes. And the data on a single customer can be just as extensive.”

Read more problems facing retail data governance here.

photo credit: dno1967b