Before internet via optic fiber became standard, the telephone companies repurposed the copper wire lines to enable internet via ADSL. Old, regardless if it’s infrastructure, technology or information storage, doesn’t have to mean useless.
We can drive a
cutting-edge electric car down a motorway originally built for polluting petrol
or diesel fueled vehicles. In the context of data, this means that
we have to harness and interconnect the treasure trove of information we already
have at our disposal. We store and manage it, in separate systems, platforms and applications,
in a way that makes it meaningful and profitable to use it moving forward.
From impossible to possible
Historical analysis, data mining, behavioral analysis, forecasting and planning, applying machine learning and heuristic algorithms to identify patterns that support growth and higher margins. It all becomes possible, when the underlying systems and applications are 1). Interconnected in a network that allows for access and performance 2). Co-exist in a common model, world view, where a Customer ID in system A, can be correlated correctly in system B, where an invoice or order ID can be matched and queried without extensive data transfer or redundant storage.
“I’m afraid I can’t do that Dave”,
HAL 9000, 2001: A Space Odyssey
The Barack Obama campaign coined the phrase for posterity. Yes, we can. New challenges call for innovation through technology to yield new solutions, even to old problems and legacy IT landscapes. We can leverage the content of existing data in systems and applications by applying tools and an approach
that introduces structure and order to the chaos of multiple, overlapping systems of record. This is called Master Data Management.
In this case this excerpt from Wikipedia explains the concept concisely;
“.. ensure the uniformity, accuracy, stewardship, semantic consistency and
accountability of the enterprise's official shared master data assets.” In
short, making sure that there are no duplicate metadata objects, and if there
is – knowing which is master, how to handle inconsistencies in analysis, and so
on. It is only when we can trust and rely on our data, that it becomes useful
and valuable. We must know what we have, and how to use it, before it can be
Connecting the dots
The second step is to make the data accessible for actual analysis, reporting, and used in the application layer, and there have been many attempts at this over the past 30 years.
The challenge is multidimensional.
- Data is stored in separate applications and systems.
- Applications and systems are hosted in disparate types of infrastructure and/or geographies.
- We choose different formats and ways to store data, depending on application type and context (e.g. mobile device app vs legacy mainframe) yet we may want to use data from both in the same analysis).
Most attempts to address this have been to extract, transfer and load data into different systems. Make copies, cache, update and pool data into ”lakes”, ”warehouses”, and ”marts”. However, the exponential growth of both systems (data sources) and data, calls for a radically different approach that allows for better performance. Enter “Data Virtualization”. Again, as Wikipedia so eloquently puts it “Data virtualization is an approach to data management that allows an application to retrieve and manipulate data without requiring technical details about the data, such as how it is formatted at source, or where it is physically located ..”. In short, remove the technical hassle to make the information readily available for application development, and analysis required to support lines of business.
Data virtualization acts as a catalyst for your existing data assets, as, ironically, although they may have been interconnected through your network before, the content was isolated from every other source due to technical limitations. The value of the connection between them is first realized when you have and combine Master Data Management and Data Virtualization to enable analysis across sources, for the business as a whole.
Metcalfe's law states that “.. the value of a... network is proportional to the square of the number of connected users of the system”. Similarly, the same applies to interconnected data sources in your business. The more sources you align the data model for, and interconnect for querying and analysis, the greater value is enabled for the business.
“.. the value of a .. network is proportional to the square of the number of connected users of the system”
How to get started
Initiatives in areas like master data management and data virtualization have traditionally, like many ground breaking technologies, resided in the purview of the megacorporations, the global enterprises, the Fortune 100 organizations. The beauty of our ever-accelerating rate of progress though is that technology is based on ideas, and ideas can be transmitted, transformed and enabled as fast as they can be envisioned and implemented. Enfo partners with market leading technology providers in (among other areas) master data management and data virtualization.
We know what the common challenges are, what pitfalls to avoid, and how to
approach the next level of information management that drives and develops your
business with a step-by-step plan. In addition, we can offer access to
these types of platforms and tools on a service & subscription basis.
Instead of having to spend enourmos sums on hardware, licenses and application
development, we have worked to make it possible to enable these capabilities
for you, powered by scalable cloud infrastructure.
The journey begins with a first step, and you must take it.
- Don’t accept the simplified ”it cannot be done”, “the system doesn’t support that”, and “that’s not part of the design” standard responses – when there’s a will, there’s a way, though it requires persistence and drive.
- Think about the way you would like to work and direct your business, rather than what your current application framework allows you to do.
- Technology is a tool, use it to work for you, not the other way around.