dataeconomy

The Economics of Data
Influencer conversations on data economics impact on business.
   11 years ago
#dataeconomyThe Economics of DataInfluencer conversations Data Economics: Driving application and business value to your bottom line
Keith A Thuerk
It seems w/ all the different types of data that their will be several different Analytic solutions in an Enterprise? Anyone else agree?
Tony Pearson
Agreed. Video surveillance data provides different analytics resource than POS transactions
Chris Saul
I'm not sure different data types is what I would measure by. It's more data usage and purpose
Dave Vellante
there are so many - more to come perhaps - vizualization, traditional BI, Excel, machine data systems
Guillermina Sainz
Agree, most, if not all, business data has value. That value changes over time and in relation to business mission, goals and operations
Keith A Thuerk I think you and I are on the same wave length. These too will evolve.
Chris Saul
So you could postulate an analytics system that used (say) BOTH video and POS data for some reason. Driven by usage of the data and not specifically because those happen to be different data types
David Floyer
In my view, there cannot be one set of analytics that will cover analyzing all questions and all types of data - there will always be a wide set of potential solutions
Karla Magana Renoud
Agree. Before you can get value, you need to first identify and define the business goal you are trying to achieve. Build your strategy around your business need, and then seek for the right analytics approach.
Dave Vellante
@MikeDonnellyJr any thoughts on how the government shutdown impacts the IT economy?
Michael Donnelly
Gov't shutdown defunds all statistics branches, so possible no data is collected & creates a missing period
Michael Donnelly
Defaulting on the debt (Oct 17-31) would be far worse and could easily send economy into recession
Elan Freedberg
For starters, in our IT-centric economy, imagine all those open tickets leaving gov't people trying to work today helpless...
Michael Donnelly
Gov't shutdown also creates business uncertainty. I'm old enough to recall certain Congress members telling us buz uncertainty is a terrible event
Michael Donnelly
Australia had government shutdown once. In the end, the Queen fired everyone in Parliament
Keith A Thuerk
RT @karenhsumar @tcrawford I agree. Practical use cases include: customer analytics, operational analytics, fraud... #dataeconomy via http://t.co/jbM1VOcg7T
David Floyer
Mmm - if has to cover more than compliance - it has to cover the strategy of what data to buy, what data can be sold, where the data is held, and how it is to be used to drive business value
Tim Crawford
Which data are we talking about? Not all data is or should be treated the same.
Allen Marin
and who owns the data and who is willing to share what is often considered proprietary data.
Elisa Ortiz
Prioritizing the "right" data has become a bigger challenge since storing data has become cheaper, we tend to keep everything
Allen Marin
Are organizations any more willing to share data with other organizations, or is that still a big issue to overcome?
Elan Freedberg
prob lots of data that won't be shared..but..there's a lot to be learned from data on social media about any company...a whole new world IMHO
John Furrier
cloud could help here but the issue will be privacy and data protection for the companies involved..b2b system might be API based to allow this seamlessly in the future
Guillermina Sainz
Definitely Cloud has been a big door opener, but organizations keep holding "vital" or valuable info on their own
Elan Freedberg
Interested in what what verticals are converting data into revenues TODAY...
Keith A Thuerk
When you mention vertical what's the context? Industry?
John Furrier
financial services is the lowest hanging fruit then ecommerce with recommendation engines then other verticals
Dave Vellante
What do people think about the notion of a "Data Czar" - i.e. a Chief Data Officer who drives data strategy, quality, governance...independent of the CIO
Keith A Thuerk
How does one ensure the data is all valid and not manipulated (it's all digital)?
Dave Vellante this is an issue of data quality - someone needs to own information quality
John Furrier
This in my opinion will be a new job that will be created more about compliance and API mgt but my concern is does this stunt innovation organically
Melissa Morales
agree that it needs a focus but with ownership and governance
Keith A Thuerk
Why would the solution be just one source is better than a shared validation method?
Levi Norman
My belief is that would create additional layers rather than enabling existing entities to expand and evolve...
Tony Pearson
Why should the "Data Czar" be independent of the CIO?
Dave Vellante the argument is the CIO has too much on his/her plate and is incentivized to keep applications running - not drive data strategies
Dave Vellante but many feel the CIO's job is to be the Data Czar
Tim Crawford
Do we need a Data Czar role for quality? Quality need to permeate throughout the layers that touch data. Otherwise, there is little/ no context.
fernando gomez
that would increase costs
Karen Hsu
If the organization can have czar, that's great. In many companies, we've seen a central group (e.g. center of excellence) agree on the specific roles and processes to ensure data quality, governance etc
Karen Hsu For Design and Production
AliyeOzcan
CDO and CIO are both required to be at the table along with Legal, RIM, Business, Privacy, and Security..
Tim Crawford
Let's not forget that there is a theoretical side of data management and practical side of it. They are not the same. Lots of theory being discussed.
Stuart Miniman
care to share some examples/proof points of practical solutions that you've seen?
Tim Crawford From a marketing/ #bigdata perspective, connecting analytics to revenue increases.
Karen Hsu From a fraud perspective, you can identify patterns of fraud in big data (combining POS, transaction, authorization data). You can then prevent future fraud based on knowledge those patterns.
Karen Hsu From an operational perspective, you can identify patterns of failure in your products and then proactively replace failing components before being notified by the customer (internal or external).
Dave Vellante
I think this is a good point Tim-- So how can organizations focus on the practical and add value - vs spinning the wheels?
Tim Crawford First, start with a clear objective. Understand the business implications and follow the trail. No value = no path.
Karen Hsu
I agree. Practical use cases include: customer analytics, operational analytics, fraud and compliance and EDW optimization
fernando gomez
I found that wo popular metrics are available to help you understand how changes within the data center can impact data center efficiency: Power Usage Effectiveness (PUE) and Data Center Infrastructure Efficiency (DCiE)
Dave Vellante
how do you see that impact data value?
Crowd Doc
How much data is bigdata?
Levi Norman
meaning what cross over volume?
CrowdChat Yes, what volume is bigdata? It changes every year with hardware advancements. There is so much more you can cramp into single machines now a days.
Chris Saul
I don't think there is an absolute number. ESG talks about how "big data" is a LOT more data than you are accustomed to
Chris Saul
So, for a small company that typically has about 100TB, "big data" might be 300TB
Chris Saul
Whereas for a large corporation, "big data" might be in the PB range
Brad Johns
On a theoretical note; just finished a good book on Big Data called "Big Data A Revolution", in which Big Data is described as the environment where the sample set for is "All".
Chris Saul
Translation: big data applies to everyone
Chris Saul
I don't think the hardware is relevant. It changes the economics of what is doable. But that's about it
Karla Magana Renoud
IDC is defining it as "deployments where the data collected (not stored) is over 100 TBs". Data sets that are not very large but are experiencing rapid growth rates of 60% or more annually are also considered Big Data under their definition.
Chris Saul
That IDC definition seems very weak. Lots of companies have >100TB but are not doing "big data"
Karla Magana Renoud I see it as a way to remove the concept that big data is only for massive companies. A small company may be experiencing big data conditions and could seek out a big data solution that fits its needs.
Chris Saul The ESG definition I quoted earlier is better for showing small companies that big data applies to them. Just saying "100TB" devlaues the term because then just about everyone is doing "big data"