Remember, Metadata is the data about the data. File creation dates, creator, size, versions, etc. are part of this. The metadata, provided there’s a manner by which it can be extracted, makes for much easier and quicker searches.
We can look at the financial approach in a few directions: Purely financial, as in predictive of the ebbs and flows of income toward an organization, and the most directly impacting of those keys to business, sales data.
One of the key details, as I see it, is that you own your data, as well as the value intrinsic to it. Why would you not, given the opportunity, let that value work for you? The question is, how do you leverage the data to gain insight to it?
Sales are hard enough, aren’t they? The process of finding potential customers, meeting with them, taking your product to them, getting a handle on their needs, and hopefully making that sale can be daunting, is challenging, and often without understandable reason. If your salesperson has any edge, it’s the value of the data. Customer buying trends, cash-flow, past sales data can lead to knowledge about what’s onsite, brand preferences, etc. Knowledge is power, and any edge a salesperson can have, by way of knowledge can provide that level of insight that turns a salesperson from a box pusher to an advocate. This data, provided by the information held within the metadata, proves that the salesperson is on-top of the account, and can ensure a trust level that goes beyond the used-car approach, toward that of a trusted advisor. This is completely the goal.
In addition, should your organization stock product for your customers, one certainly can pull reports to assure that stocking follows the protocol assigned to the customer, but with a critical eye toward over-stock. This historical sales data ensures that only appropriate money is spent to do this stocking and no more than is appropriate. Again, this will affect how accurately your organization is able to fill those orders in a timely manner, and how consistently they’d need to be restocked.
On the financial side of the equation, the impact to the way a company does business is critical. We can look at available cash-flow as a good example. This is not just a function of AR/AP, but also order-entry and inventory. Should an organization wish to know about how and where to invest in itself, it will always need to know the timeliness, and historical payment schedules of their customers, offset against orders in the pipeline, and potentially, those orders that are high probability of coming through.
In addition, let’s imagine your organization is in acquisition mode, and the company must compile this type of information against the general ledger for multiple differing organizations… Would it not be beneficial to draw the same type of requisite financial data against all P&L statements from all valid GL’s? Very few tools have strong reporting capabilities against disparate databases, and let’s face it, if you acquire a new organization, chances are that they’ve run their accounting on differing platforms, with, chances are, differing databases underneath. So, the compilation of this data against these differing platforms becomes increasingly, and exponentially more difficult. A solid tool, designed to connect the datasets, pull out relevant data, and present these data into a report that means something meaningful, at a glance, are few and far between. A few that spring to mind are Splunk, ELK, and some Oracle database tools. These run the gamut from OpenSource to fully licensed. To my mind, the quality of that reporting is augmented by the capacities of the software tools, and the ease of which these tools may be leveraged to present that data easily, and in a quickly understandable nature.
To my mind, this sales/financial data, while the analysis may be difficult, is the most mission-critical data to leverage in order to get a healthy state of your organization and determine the feasibility of acting on it.
I’ve really enjoyed writing this series of postings on the key values of Metadata, and hope to hear from you, dear readers, some of your examples of how your backups, your financials, your hardware/software performance data, and any other aspects that could be relevant may be or have been affected by how your organization has leveraged the metadata that presents this information.
