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Big Data I just don't get it, are any SMB firms finding value in leveraging it, whatever it is?

I have tried to make it through webinars focused on big data. What does this term actually mean? What is the value of what they call "unstructured" data? How can an SMB get and leverage information on things like the social media activity of customers and its own employees?


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(CFO, Empower2adapt) |

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Topic Expert
Barrett Peterson
Title: Senior Manager, Actg Stnds & Analysis
Company: TTX
(Senior Manager, Actg Stnds & Analysis, TTX) |

First forget "big", as size will vary hugely with the size and complexity of the business. For SMB think primarily higher volume data like POS and shipping informantion and "unstructured data", including sensors in a manufacturing process. Unstructured data, or non-traditional data can also include social media metrics, many of which do not correlate very well with more prosaic metrics like "sales". The idea is to use what you know electronically to provide customer services that is more timely, more specific to individual customer needs, and more likely to drive better brand acceptance and repeat business. Too much focus on the tools and activites, and not enough on how it can drive your business.

Topic Expert
Bob Scarborough
Title: CEO
Company: Tensoft, Inc.
(CEO, Tensoft, Inc.) |

A few thoughts that might be helpful:

1) At this point - since it is a hot topic - there is a lot of noise out there and some pretzel-ization (folks twisting themselves into knots to try and align with the hot topic) going on - so not all of the information out there relates to what is the core of big data.

2) Geoffrey Moore does a nice job of writing about the technology and the adoption of it:

3) I think of it as non-transactional, non-traditional data. Basically you start collecting additional data often without knowing exactly what you are looking for (sort of). It is un-structured - meaning it is not like an accounting transaction that has an identifier (say invoice number) and other validated data that fits a pre-defined model.

4) One example of this type of data - for a cloud financial software company - is to think about saving every key stroke a customer does online with your application. The traditional (transactional) data in the accounting system is what you enter (for example an invoice). The 'big data' component tells you every place in the user clicked on the screen - what order they clicked on things - what they clicked on multiple times - how long between clicks - and so on. The general goal for saving this 'big data' is to analyze it to see if the software could be easier to use or easier to learn or more engaging - not to save the entered data as a transaction.

5) For a SMB you might have a couple interests here:
a) If you are a technology company this may be something that helps you win or keep customers, improve or track security, or even find ideas for new systems and functionality.
b) If you are a company where security is mission critical (beyond what everyone wants) you may be adopting some new application(s) that applies big data models to what people do in and around your systems.

Bob Scarborough

Mark Hirsch
Title: CEO
Company: CreativeWorx
(CEO, CreativeWorx) |

Embracing Big Data can streamline internal operations to increase revenue, reduce costs, improve ROI of other existing systems, and enhance quality of life for your employees.

Imagine if there were a system that could automatically capture and intelligently process the volumes of data produced by your employees simply while they worked.

You could see real-time data about
- which clients consumed the most time from your employees
- what software being licensed is actually be used...and by whom
- what types of work is your company's most profitable and least profitable

Professional services firms could have automatic timesheet drafts that feed their existing workflows and financial/ERP platforms. Those systems are only as effective as the data going in...and the data shows that current timesheets are often late and extremely inaccurate.

With real-time data, managers and executives could make effective decisions that reduce administrative costs and reduce the time applied to less profitable endeavors.

Simply put, big data analysis allows you to automatically extract more insight from existing (but untapped) data streams to help your company be more effective and profitable.

Mark Hirsch

David Buley
Title: Chief Financial Officer
Company: Association of Independent Schools of NS..
(Chief Financial Officer, Association of Independent Schools of NSW) |

I, like you I think, are wary of the hype surrounding that phrase 'big data'. Its taken on a life of its own, and I try not to use it in presentations anymore because it makes me sound like a pretentious know-it-all. Nevertheless, despite the label, it does represent an opportunity for companies to use computing power and contemporary data visualisation tools to develop insight into their operations by exploring data sets and connections not previously achievable. By now you realise the unstructured data represents snippets of information normally associated with social media (twitter, chats, posts, photos, videos etc) where people are expressing an opinion. You can't ignore this, these people might be customers. It seems like 'everyone' else is on board with big data except you and you're standing at the foot of a very large mountain which is growing daily. Don't worry - most people are faking it - they are just as confused. My advice would be to learn what you can, get involved so you have a personal relationship with these forums and media. Get your team together and explore what types of data-initiated insight might be available to you. This may require changes to your system but you have to start somewhere. You can't solve new problems if you don't change something. Then, walk towards the light.

Ron Davis
Title: HRIS Analyst
Company: NRDC
(HRIS Analyst, NRDC) |

Big data is only useful in the hands of skilled people who know how to make use of it. There are so many ridiculous assumptions to be made that are invalid and simply waste time while leading to dubious results. First find the professional who consumes and understands data, then consider the tools and data to consume.

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