Big Data – An Infographic Perspective

Big Data – An Infographic Perspective.

Big Data – Who will find the patterns of value?

Big Data has great promise – no doubt that we are on the brink of discovering innovative ways to make a lot of money due to the ability to consume and analyze a greater volume, velocity, and variety of data than ever before.

The question, however, is who will make these innovative discoveries?

Can the innovation be made by a kid in a garage, a college kid in his dorm room, or a talented IT professional dreaming of a start-up in his free time?

On the one hand, the answer is NO – the college kid in the dorm will NOT be changing the world via big data the way Mark Zuckerberg did with social networking. Why? The reason quite simply is because “Big Data” requires DATA and a lot of it and in potentially many different forms.

Data is not free

In fact, there are billion dollar businesses that are essentially data companies – they sell raw data (and analytics on it). I’ve even worked at one in my time. OK – Some of that raw data is free but much of the data is not. The sheer volume of data is prohibitively expensive to acquire for a college kid to start to experiment with. Additionally, some big data use cases revolve around social data that sites like Facebook can use to make money (data is why Facebook has such a high valuation). Did you think Facebook gives away their data for free? If the college kid can’t even get his hands on the data then the game is over before it even starts.

On the bright side, however, cloud computing infrastructure as a service and pay-as-you-go pricing provides affordable infrastructure for the college kid. Powerful infrastructure is also a pre-requisite for Big Data – but it’s not a barrier for the college kid.

It goes back – again – to access to data.

The majority of the big data discoveries will come from big established companies with the resources to acquire it.

Agree or disagree? Actually, proving me wrong would make me happy.

Application Portfolio Management – Notes & Mindmap

Application Portfolio Management: TIME for the Application Masses

• Findings
  • Large inventories of small applications can often be categorized rapidly by frequency of use.
  • Many infrequently used applications can be retired or consolidated.
  • Proactively proposing retirement can accelerate portfolio simplification
• Analysis
  • Big, complex applications are often a fairly small percentage of the total application count., support a lot of business value, and merit a detailed analysis
  • How can we economically categorize and overhaul the thousands of smaller applications that form the rest of the portfolio?
  • ” Application-hunting license,” prescreening applications by usage and requiring user involvement in creating appropriate life cycle strategies.
    • Create a routine process that will rapidly align the thousands of applications into tolerate, invest, migrate and eliminate (TIME) categories — ideally driving extensive application elimination
• Application Hunting
  • Start this routine with any applications that haven’t been accessed in a year, then systematically bring the time down to nine months, then six months and then three months.
  • It’s Rare that anyone thinks of retiring applications after task is done or the project is completed. In extreme cases, none of the people who used the application remain with the organization.
• Send out a message listing five to 20 applications that have not been accessed in several quarters.
  • In the case of nobody responding, the exercise is straightforward to retire the system
  • Otherwise ask How often is the application used? Could you live without it? Is there another way to get that job don
• One less system to maintain, fewer licenses for which to pay maintenance fees, and less storage and power being consumed
• “mock” retire the system — that is, bring it offline for a full quarter, and if no one complains, then officially retire it

Application Portfolio Management: Maximizing Value

Application Portfolio Management (APM) is about maximizing the value of the applications running your business.  The goal is to achieve beneficial changes that improve the balance of value to supported cost risk.

Without an APM practice, the unmanaged portfolio of applications grow stale. This may be in the form of higher operating costs to “keep the lights on” for the application, weak service level and support, or obsolete technology – to name a few. The key here then is to methodologically and pragmatically assess all or a subset of the applications top-down in the business in order to devise strategies and define projects and request funds.

We begin the process by assessing key factors of each application in order to categorize each application. Ideally the scope is all the entire application inventory but it may be segmented based on current strategic business initiatives with a process, risk, cost, or value perspective. There are various methods to categorize the applications. A popular format is based on the 2X2, 4 quadrant matrix. An example is the “TIME” (Tolerate, Invest, Migrate, Eliminate) method as defined by Gartner.

T – Tolerate applications that provide good enough business value but may have an old architecture or not be well integrated. Without APM, this is probably the largest category.

I – Invest in strategic or newer applications in order to increase value and use.

M – Migrate technologies that have high business value but have issues the with people, data, or technologies that support it. The technology may be unsupported or people may be on the verge of retiring with a declining pool of replacement skills.

E – Eliminate applications that no longer provide sufficient business value.

Once each application has been categorized then define a strategy and high level set of actions, and create a business case and project charter. Also, add these newly defined strategies to the overall future-state enterprise architecture plans and roadmaps.

Over time, the application portfolio balance should shift to a greater percentage of “invest” applications with a lower percentage of tolerate and eliminate applications. This will result in a greater proportion of IT spending to business value and growth based projects  – and that’s the goal.

Top 3 Drivers for an IAM Business Case and 8 Presentation Tips

In this post, we will discuss the top 3 Drivers for an Identity and Access Management (IAM) Business Case and 8 Presentation Tips.

Who: As always, consider your audience – who will be most interested and in what driver. At a minimum, include the following teams and see the benefits through their eyes:

1) IT Operations Management 2) Security and Legal teams 3) Business (revenue focused) Managers

What (the drivers/benefits):

1. Efficiency – The ability to do more, faster and with less effort. Examples include automating access removal when someone leaves a company, reduction of helpdesk calls from automation of password resets, SLA improvement, and quicker consolidation of infrastructure.

Primary audience: IT Operations Management

2. Effectiveness – Doing the right things and doing them well. Examples include more accurate reports, savings from reduced regulatory fines from inaccurate reports, better general consistency and automation of reports, better customer and auditor perception.

Primary Audience: Security and Legal Teams

3. Agility – Change faster with less effort. Examples include the reduction of effort to form business partnerships (and thus encouraging more partnerships), reduce the time to integrate a newly acquired company, and improved customer service.

Primary Audience: Business (revenue focused) Managers

Socializing and Presentation Tips

1. Emphasize non-quantifiable benefits over ROI calculations. The reason is because ROI calculations are based on assumptions that can often be easily challenged, derailing the entire business case if successful. Only emphasize ROI if you are comfortable sitting in front of the CFO for 20 minutes going through the detailed assumptions and calculations. It’s a safer bet to stick with non-quantifiable benefits. If you must include an ROI, be sure to include others in the assumptions and calculations.

2. “Road test” the business case presentation in one on one or smaller meetings in order to get feedback and improve your message.

3. In the presentation, spend more of your time on the expected benefits as opposed to the why, how and technical jargon, which often only detracts focus from the main drivers.

4. The overall format should include at a minimum one slide for the following: problem statement, who was involved in the business case analysis and objectives, proposed solution, expected benefits, high level plan/options and costs, and an Appendix (assumptions and calculations).

5. Present in a professional, conversational, and competent manner

6. Know the material well (more than what is just on the slides)

7. Formally present for 20 minutes and then answer questions and have a conversation for another 20 minutes (often the most important piece)

8. Speak with conviction and above all else, honesty.

So Why Field Notes?

Reblogged from Dr Jerry A Smith:

• 

Those that know me will contest that I tend to take a lot of notes. I do so because I truly believe that to remember is to record. This quote, "I'm not writing it down to remember it later. I'm writing it down to remember it now" really put this practice into perspective for me. As such, most of my field notes never see the light of day, not even for me.

Read more… 182 more words

The "Notes and Mindmaps" section was inspired by Dr J's blog of "Field Notes".

4 Ways IaaS Cloud Computing Will Reduce Your Costs

1. Disaster Recovery – Cloud providers such as Amazon AWS offering “pay as you go” pricing enable reduced cost for disaster recovery. Essentially, one only pays when disaster happens and a recovery is needed. To be more accurate, the 24/7 activity of replication and storage of data from the production environment to the DR environment is the fixed cost. At the same time, however, the application and data servers do not cost a single penny unless a disaster happens, in which case the servers are started up. Even if a disaster lasts for months (e.g. Katrina), this is still considerably less expensive than an in-house data center that must purchase all the hardware upfront for the application and data servers.

2. Batch Computing – Batch applications often follow a predictable “batch window” of high and low processing requirements. For example, nightly batch processes may require 1000 servers of processing to complete it’s processing from 12am-8am before the next business day starts. These 1000 servers must be purchased up front and may not be used (or used very little) during day-time business hours, resulting in a very low CPU utilization rate of 33% (8/24).  With IaaS cloud computing and the ability to scale (or auto-scale) when needed, the CPU utilization rate is theoretically 100% or realistically at least in the 90s. Major savings.

3. Short-term Web Site – For example, a marketing professional may create a dedicated web site for a product. If that web-site is mentioned in a commercial  during the Super Bowl with 100M+ viewers, there a good chance that web site will get hammered, potentially with 100′s or 1000′s or more  unique hits within a few minutes, potentially requiring 100′s or 1000′s of servers. A few days after the Super Bowl, the  marketing web site requires 2 servers for the rest of the year. Again, with a pay as you go and auto-scaling capability, the cost savings in comparison to traditionally purchasing all the equipment up front are through the roof.

4. Test & Dev – Cloud computing is also cost effective for test and development environments that may not need to be running 24/7. Again, pay only for the time the system is running.

IaaS Cloud Computing will not always reduce costs

It’s important to call out that IaaS Cloud computing may not be cost effective for large business steady state workloads for many use cases and may even be more expensive.  I predict, however, this will change due to improved automation capabilities that enable IT Operation teams to perform more efficiently. The technology of automation capabilities are still lacking and not yet mature enough to provide real steady-state savings. Examples of automation capabilities include automated patches, backups, database replication (e.g. Amazon AWS RDS), and the ability to quickly deploy and configure  a complex, integrated environment of web, application,  data and network components components in an automated fashion. Again, the tools exist but are still several years until mainstream adoption in my opinion. Put another way:

Sufficiently mature and integrated automation capabilities will be the tipping point for mainstream enterprise adoption of IaaS Clound Computing. We are still several years away from this reality. Do you agree or disagree? Your thoughts are welcome.