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Found this article from Chris Taylor interesting where it states:
Big Data success is process-based
So how important is process to Big Data?
Antoine THOMAS Accepted Answer
Talend, one of the leader of Big Data solution, includes Bonitasoft BPM solution to create processes around data management.

Processes are the root of Big Data management, this is clear !
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Emiel Kelly Accepted Answer
Every company has processes. For some it's not important to have grip on these processes, but for a few it is. To make a process perform a lot of aspects are needed.

One of these 'enablers' of a performing processes is information. Information for execution, Information for managing an information for Improvement of processes.

Bigdata in itself is just a bunch of bytes. It might be processes where it is used for a purpose. So I think I would say yes to this question.
Common Sensei at Procesje.nl
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Phillip Rhodes Accepted Answer
Yes and no. Is peanut butter worthless without chocolate? No. Is Chocolate worthless without peanut butter? No. But are they better together? Clearly.

Same here.

At the end of the day, the point of "big data" analytics is to reduce uncertainty. Reducing uncertainty allows better decisions to be made. Presumably those decisions are being made within the context of some process, whether it's automated or not. So use of "big data" probably always has value.

But when you tie process optimisation together with your big data analytics, use a continuous improvement / Kaizen approach, and understand how to connect knowledge to processes, then you have a setup for maximizing the benefit of all of these techniques.

And on a sideways note: an organisation should also have a process for choosing big data projects - evaluating project proposals, evaluating risk, determining the probable return, and selecting appropriate tools.
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Max J. Pucher Accepted Answer
Blog Writer
Once more: both process control and Big Data can be used to some extent in closed physical systems such as in manufacturing but not in complex adaptive systems, meaning economy, finance and doing business in general.

Big Data propopents sell the illusion that a lot of data treated the right way make the future predictable. There is no such thing. It does not even make anything more probable. Causality is the only thing that would make such predictability happen and as there is no extractable causality in complex adaptive systems that is a foolish undertaking. There is also no direct link between correlation and causality one of the most common mistakes by people using statistics.

It is utterly ridiculous to propose that Big Data reduces uncertainty. In addition to the normal uncertainty about emerging effects in complex adaptive systems it adds the uncertainty of worng models, flawed data collection, flawed data filtering, flawed data processing, irrelevant correlations being seen as causality and the relevant data being obfuscated by too much data. Big Data increases uncertainty no end.
I am not presenting an opinion here, but this is verifiable scientific understanding about complex adaptive systems (Holland, et.al.).

Data does not contain knowledge, as knowledge is about applying experience to every step of an evolving process to achieve its goal. The data-information-knowledge-wisdom pyramid used by Russel Ackoff demonstrates that. Wisdom is about which knowlegde to use and which not when it comes to the crunch.

There is only thing that Big Data enables and that is to collect as much data as possible about an individual and yes, that allows a lot of conclusions to be drawn. Obviously no one wants to admit to that so they talk about predictive analytics, when they need to talk about a total loss of privacy. You think a government, an insurance company or bank will use this information gathered to your benefit? Big Data is a try to replace human service interaction with automation but only to one end and that is to increase profits. Don't be so naive.

Clearly if all the data collected about a person is used within a process then that process can be tailored more to fit that one person. Once again, you think that will be to the benefit of that person, Don't be so naive!

So Big Data does not improve anything and it clearly does not improve processes, especially because Big Data processing is so slow that it is impossible to run it in a time frame that will make use within a process practical. Big Data can also not be used for improving processes and it is not needed because process data aren't big. Human intuition and knowledge/wisdom improve processes and nothing else.

Add a Big Data illusion to the illusion that a process guarantess outcomes and what do you get? Still an illusion.
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Big data, little data... the idea that data doesn't drive discovery (that is, increase knowledge) is a pretty interesting claim. Scientists, take note: your entire approach to learning appears to be wrong.

Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there'. (Points to anybody who gets that reference.)
  1. E Scott Menter
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David Chassels Accepted Answer
Process creates data Process uses data long live “small” data!

As a business person I really struggle with this “big data”? I think Phillip puts into an understandable context but really feels like just a lot of “small data” for the ordinary business – unless you are a telephone company…… where interestingly we did a POC handling requests for information from police and it was all about process and small data…once the big data found the small data…..which was “search” not process even if it was triggered by a process.
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Christopher Taylor Accepted Answer
Blog Writer
Max, I'm unable to really understand your response in the context of what I see and hear every day. I realize you're a big proponent of dynamic case management, but the fast-digitizing world has many, many (many...) examples of where large and complex data sets are used to predict outcomes based on choosing and executing specific processes from the many choices businesses have (dynamic or not).

As far as Big Data reducing uncertainty, I think you're wrong on that one.

While you may think Big Data is slow, that statement is a bit confusing...do you mean Hadoop batch processes are slow? There are many examples of where data is being filtered as it is streamed, stored temporarily in in-memory data grids, and used in what a consumer would feel is real-time.
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Phillip Rhodes Accepted Answer
The thing is, "big data" is, in many ways, just a buzzword. There's no fixed amount of data that qualifies as "big". When I talk about "big data" I really just mean the use of "big data tools" whether of the newer breed (map/reduce based, Hadoop, etc.) or traditional HPC (MPI, OpenMP, etc.) regardless of the actual data size. To my way of thinking, the distinction is strictly an economic one: when a problem that you're trying to calculate a solution to won't "fit" on a single computer, and a cluster approach (whether Beowulf, Hadoop or "other";) is cheaper than a forklift upgrade, then you use a cluster and the pantheon of tools that are typically referred to as "Big Data".

To Max's point: I agree that the ability to do predictive analytics in a CAS is limited. That's pretty much a tautology, actually. But, not everything is a Complex Adaptive System.
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Co-rrect. Not EVERYTHING is a complex adaptive system.
  1. Patrick Lujan
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Ian Gotts Accepted Answer
I had a very interesting discussion with a Gartner "Big Data" analyst who was speaking at a BPM summit. The summary of the conversation

"Big Data is cool, exciting and growing. BPM is not. Whilst Big Data needs BPM to be really effective it is doing pretty well on it is own. So why would the Big Data guys saddle themselves with BPM and slow themselves down."

Sad but true
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True, it's one of the bingo buzzwords du jour. Big Data reminds me of CRM (Siebel, PeopleSoft, JD Edwards) 10, 12 years ago this time. A lot of people are going to spend and lose a lot of money before this stuff shakes out and it gets placed in the stack in the right place(s).
  1. Patrick Lujan
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Christopher Taylor Accepted Answer
Blog Writer
Ian, not sure I agree. I know you have a very deep BPM background and a strong perspective. I also know that too much of the spend on Big Data has lacked roots in how organizations actually operate, meaning that we end up with insight that isn't useful or insight that can't be used. If organizations could first identify what process needs to be improved, scrapped or created because of the output of crunching large (or small, but otherwise very important) digitized information, they would be far better off.
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Scott Francis Accepted Answer
Blog Writer
I see a lot of focus on Big Data, and the massive amounts of data out there. Saw a quote of something like 25B bits of data a company collects every day that they want to analyze.

So, here's a thought. The issue isn't having and dealing with lots of data. The issue is separating signal from noise. wheat from chaff.

Data is useless without context, no matter how much or how little you have. Process is one kind of context, and some might call it useful...

The challenge to data and information is that we have too much. Maybe we should figure out how to process more. Or maybe we should figure out how to collect more relevant information at the source, and to store less irrelevant data to begin with. Focus is more important than data volume. Quality more important than quantity.

This is all motherhood and apple pie. And it is obvious when you consider that a lifetime of video is uploaded to YouTube every minute of every day. And yet, there are only a few videos worth spending your time watching. As the amount of video grows, you can be even choosier about what you spend your time watching...
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Kathy Long Accepted Answer
Blog Writer
Back to the question, "Is Big Data Useless without Process?".

The answer is an unequivocal "YES". If an organization wasn’t doing anything with data/Big Data, then process wouldn’t matter. However, nothing can happen in an organization without both. They require different skills sets to address how they are used most efficiently by the organization, but the organization must have both. Data requires process and process requires data. I don’t think process requires “Big Data”, however that’s defined, but it must have data. The determination of whether process is essential to “Big Data” is certainly not linked to whether BPM is exciting or not. Sorry Ian.
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Kevin Parker Accepted Answer
Blog Writer
Gosh this is a big topic and worthy of a treatise all its own. How to be succinct?

Processes and data are engine and fuel of business. An engine without fuel is will take us nowhere. Unburned fuel is just energy hanging around with nothing to do. Process without data ... well, you get the analogy.

Data has gone from being a facsimile of an entry in a ledger (60's flat files), to an online archive of transactions (70's indexed files), to a connected catalog of information (80's databases), to a cross reference-able decision support system (90's relational databases), to a consumer facing sales tool (00's web-apps), to a mash-able source of public and private insight (10's mobile apps).

The trajectory of data is moving from simple audit-able, transactional record keeping to empowerment of consumers and business leaders. The further along this continuum we move the connection between the data's purpose and the ways we exploit it become ever tenuous.

http://www.cosmopolitan.com/cm/cosmopolitan/images/Op/facebook-breakups-11410-lar.jpeg
An example: The much quoted FaceBook Status change graph shows how many Facebook users changed their relationship status to "single" on each day of the year. Those making the status change are telling their friends about what is new in their life. Aggregated together the data tells a story to our society, its pressures, its trends and that weekends put a lot strain on relationships.

See also Google "Flu Tracker" where Google tracks searches looking for flu symptoms to predict where epidemics are likely to break out.

This is "Big Data" in action. My belief if that those with a Sherlockian mind that can sleuth out insight from the peaks and troughs of aggregated (ie. big) data will be the new superstars of our business. Perhaps CIO might finally mean Chief INFORMATION Officer, or at least we might create Chief INSIGHT Officers.

Those insights will lead to new processes. Business leaders will learn from the C-Insight-O that when there is a dry winter in California hotel room rates increase in Hokkaido so they need to ship suncream to Japan earlier. From these insight will develop new inventory management processes.

Just like Amazon deciding to ship product before you buy!

So what does all this mean?

We will get the most out of Big Data by being completely free of process. The "creativites" who will see meaning in data will have the most abstract role that there has ever been in technology. But from their wisdom we will optimize how we run our business by introducing processes that exploit the newly uncovered truths.

For me this is the most exciting time there has ever been in our industry. What problems we will solve! What conundrums will become commonplace? How many unknowables will be ubiquitous facts? Once insoluble quests will be daily tasks done on our wearable device.

Process consumes data, data delivers insight, insight improves process. How sweet is that?
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E Scott Menter Accepted Answer
Blog Writer
Data (large, medium, or small) is the noun. Process is the verb. If your data is "apple", process determines if you are throwing, slicing, peeling, baking, mashing, chewing, rinsing, carving, or picking.

I'm sure that clarifies the matter. :)
http://www.bplogix.com/images/icon-x-medium.png Scott
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That's why the above mentioned Gardener says it's growing; it's an apple!
  1. Emiel Kelly
  2. 2 years ago
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Bogdan Nafornita Accepted Answer
Big Data is a tagline for technology vendors that seek to sell hardware and middleware.

There are several layers missing (still!) till you get to the top of the tech stack, which is Business Processes: there's a fundamental lack of focus on how to PROCESS the data, how to ANALYZE and extract meaningful insights from the data (Data Scientists positions are made up on the spot, lacking both a statistics / econometrics background and a commercial background), how to consistently EMBED insights into a cheaper decision making process etc.

So, yeah, big data is useless for now, because it has not yet reached consistent business processes.

Again, I bring you the example of the biggest data owner in the world (Google) and its absolutely deplorable business processes around end-user care. Yes, they can correlate/analyze data into insight packages sellable to advertisers (hardly a sophisticated business process per se), but the interaction with their end-users is pitiful.
Managing Founder, profluo.com
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As far as I know, the first and oldest user of “big data” is the high-energy physics. That usage of “big data” is to find (in a scientifically provable! way) some dependencies and thus understand some processes in the nature by proving or disproving some theoretical models.

What is cool with the recent use of “big data” that it helps to not only understand, but also to change the majority of processes (thus close the improvement/optimisation loop).

Thanks,
AS
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