Why Automating access to your critical Data is Important to you.

When we talk about data accessibility in terms of critical thinking, a question we often ask our clients is: Why do you think access to your critical data is important?  The answer is rarely obvious and most often that the client typically doesn’t even have access to critical data, or else doesn’t have access to it in time to take action.

At this point, many solution providers will immediately jump to the “How” of their solution, and dive into all the cool features and bells and whistles, all without fully understanding why accessing data efficiently is important to their client, much less what decision the Client needs it for.   Eliciting this answer informs your Client’s most important and relevant use cases around which a new approach makes perfect sense.  So let’s give it some context before we dive into the “how.”

Accessing your data efficiently is about more than just finding and manipulating data from a single source or even heterogeneous platforms. Decision makers need to access the data to develop and deploy business strategies.  Even more importantly, we need to access critical data in time to take tactical action when warranted. The ability to see your business data in real-time also lets you check on the progress of a decision.

Data Virtualization is one solution to get at your critical data in real-time, even if it is scattered across multiple sources and platforms.

The first thing you need to know as a Client is that you won’t have to recreate the wheel and replace one cumbersome approach with different cumbersome approaches. 

Connectors, connectors, connectors.

Typical elements of a useful Data Virtualization paradigm are up-to-date “Out of the Box” data connectors, platform specific protocols, useful API protocols and API-specific coding languages and thought to whether modified data would be written back to a source or new data-set. 

An example of the latter would be updating your balance in a Customer Care web application after making a payment online. In this example, the following is assumed:

• There are 5 offices across the world. They all speak different languages and have different platform protocols
• Currently data is scattered in various sources (i.e. cloud, excel, and data marts)
• It takes too much time to combine the scattered data sources into one report. Transformation is a long process (with many steps) that turn raw data into end-user-ready data (report-ready for short).

With the right Data Virtualization tool, or Data Integration platform, you can consume data in real time.  Without waiting for IT, without making copies, and without physically moving the copied data.

Since Data Virtualization reduces complexity, reduces spend on getting at and using your data, reduces the lag from requesting data to using data, reduces risk from moving and using stale data, and increases your efficiency as a decision maker, data virtualization is almost certainly the path to take here.






This is a guest blog post and the author is annonymous.

Tech Debt Out-of-the-Box ... "And all the Ills of Integration-kind were Unleashed"

We often talk about having cool capabilities “out of the box,” which is a good thing. That means that you don’t have to do anything but a quick install and you can start using the feature. That is, unless you are talking about Legacy Integration Software (LIS), in which case, when you first “opened the box,” it began spewing Tech Debt before anything else happened. All the ills of integration-kind were unleashed. Years later, you are still prisoner to your Pandora’s Box.

You launch a new project using Legacy Integration Software. First open Pandora’s Box:
        1. Install new instance and all related tools
        2. Apply 64 patches; you can implement the work-arounds in a few months when you start actually developing the integrations.
        3. Send team to a few weeks of Legacy Integration University
        4. Better hire a few consultants, too.
Tech Debt abounds already!

Below is an actual post on a recent Integration Consortium’s LinkedIn Group discussion. The topic has to do with updating customer communications to a standard XML format as opposed to legacy file ftps. The Legacy Integration Software limits the options. Adding XML to the mix means that the LIS needs additional work.

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"We already have in house Informatica footprint. So we plan to use that for generating all outbound files. Here is the concern.
We have two options for generating these files.
1) DB -> Informatica -> Standard XML -> XSLT -> Custom File
2) DB -> Informatica -> Custom File
First option provides the benefit of standardization/canonical information model, long term migration path of custom files to standardized xml, and less development since only one Informatica process is required and all custom format are through XSLT.
Problem we see with this approach is the potential performance issue; outbound XML file size in some cases is more than 1GB due to XML tags while the corresponding custom file is a 50MB or so. Second issue is an additional hop that makes support/troubleshooting activities a little harder i.e. where/why a file generation process failed."
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No one should have to think about these things. Agile Integration Software (AIS) like Stone Bond’s Enterprise Enabler would require only a single process for this solution. The differences in the mapping and destination format required would be handled by passing the customer ID, which determines either which map to run or passes variables directly into the transformation engine at run-time to modify the actions. The same process can alternatively step through a standard XML, although the value of doing that escapes me. Performance would not be an issue, and troubleshooting through the streamlined solution is simplified. Stone Bond customers implement such B2B transactions using DBAs as opposed to specially-skilled programmers.

Why, in the twenty-first century, do you have to jump through hoops to get data wherever you want it whenever you want it? Here we are, musing over the “leading edge” Big Data hype and allocating millions of dollars for pilot projects next year, when we can’t even get clean, quick, agile data exchange with our customers and business partners. Does that make sense? I don’t think so. Isn’t it time to embrace twenty-first century technology and start eliminating the Tech Debt you have accumulated instead of continuing on a path that parallels the national debt?

Agile Integration is easy to try out. You do owe it to your shareholders.

You've Got Big Data! Use it in the Cloud… Virtualized!

I get why Big Data is capitalized. It's even getting to the point where it could rate all caps, "BIG DATA." The part I don't get is why this is such a new big deal. Big Data has been around for a long time. Just think about the huge bodies of data that scientists have been gathering and analyzing just fine over the last who-knows-how many years.  The explosion of social media certainly brings a new dimension on rapidly growing, potentially valuable data, and poses the challenge of making it as valuable as the Big Data you already have.

The most valuable information in your company is probably not social media, but rather your corporate data. What about all that Big Data lurking in your corporate systems, data warehouses and across your multiple divisions? Your corporate Big Data is not like the scientific nor the Social Media Big Data:

o It's not in one place like the scientific data or the Social Media Cloud.
o It's across different organizations and geographies
o It looks different each place

I think of the Big Data focus as being on how to make it useful, not just for business analytics, but more importantly, to make it actionable to your elastic and agile enterprise. This means your solutions needs to be something that can be configured in very short time frames, which means eliminating custom coding. 

In order to be effective at leveraging your Big Data assets, integrating Big Data sources must be treated with streamlined transformation, federation, and virtualization, in an extremely unified architecture. This is necessary to provide the high performance requirement and is achieved by eliminating the classic steps through multiple components for extraction, transformation, staging to federate, and transforming again to align to the destination. It also requires the ability to address complex data manipulation with inline quality checks and error management.

o Access data from multiple disparate systems
o Leverage premises based and cloud based data virtually together in your own cloud
o Federate as data is being accessed from multiple sources, lookup tables
o Virtualize your data. Make it consumable by applications on premise or in the cloud live, virtually. This means that there is never a copy made of your data. (Of course, if you should want to actually send data, that's fine, too!)

Now, about that cloud…

Leveraging the cloud brings a host of opportunities not usually found within the walls of a corporate enterprise. The cloud brings an elasticity to try new architectures, explore new applications and meld your legacy data with Social and New Media for breakthrough business tools such as Predictive Analytics.

The trouble with the cloud is that we are concerned about maintaining the security of our data.  We feel this new technology should bring a tectonic shift in the way we think about integration to the cloud and in the value it can bring, without paying the generally accepted price.

To the best of my knowledge, there is only one product on the market that actually can do this: Stone Bond Technologies' Enterprise Enabler. With Enterprise Enabler you have the solution for Federating, Virtualizing and Leveraging your Big Data in the cloud.

o Your Data remains your data. Your data is never physically copied or placed to the cloud or anywhere along the way. It is accessed, transformed, aligned and virtualized in a single execution
o The data integration is end-user aware. The end user of the cloud application will see only the data he has authority to see.
o Your data is immediately actionable. Users of the cloud applications can update and add data on their screens, and the data is passed back to the source for updating, provided the user has authorization to do that.

A use-case example is a financial institution using this technology to supplement the Salesforce.com data with on-premise information that needs to be seen by the loan personnel alongside the cloud data.