Data-Centric Decisions Are Existential To Your Business

Entrepreneur and leader in B2B solutions in both U.S. and Europe; Founder and CEO of Aparavi Software Corp. in Santa Monica, California USA.

Apart from building a team of rock star employees, one of the most important decisions business leaders can make concerns data. Years ago, upon the advent of companies like Google and Facebook, it was said that oil was no longer the world’s most valuable asset — but rather, data was the new oil.

Today there is a very different analogy: Data is water. It is no longer an asset; it is a necessity. It’s the very lifeblood of an organization. Without water, nothing would exist. Without data, a company wouldn’t exist.

The decisions we make about our data are therefore existential. But most of us are making decisions blindly, or not making decisions at all, because we have little understanding of or visibility into our data.

In today’s data chaos, business data is created, moved, copied and versioned across many diverse and far-flung systems. It’s in the data center, various clouds, the edge and the endpoints of the network. It’s in structured databases, semi-structured email applications and unstructured streams, pools and data-lakes. It’s on places it probably shouldn’t be, such as file-sharing sites, social media and mobile devices.

Data Demands And Value

When you know what you have and where it is, you can capture, categorize, manage, retain, migrate, reduce and reuse information. These capabilities are critical to data decisions, including regulatory and corporate governance, legal data discovery, forecasting, controlling costs, minimizing risk and protecting intellectual property. A net result is both saving money and making money with your data.

The first step is to find what you’re looking for, and it’s often the most difficult part. In this distributed data world, you’re looking for a needle in not just one haystack, but several haystacks spread across several different global barnyards. You may need to find specific keywords in the content of a file or find a file by its metadata, such as date, application and version, or find data that is high-risk, outdated, redundant or without business value.

Effective data discovery is complicated because of sprawl and diversity of environments. Most search tools are limited to the platform for which they were intended and are bound to their siloed systems. This isn’t useful if you don’t know what you’re looking for, or you know what you’re looking for but don’t know where it is. Some have a Google-like search but limit you to contents and/or other cursory metadata fields, insufficient for large enterprise use where there may be 50 variables or more (e.g., finding and handling regulated data).

Finding is fine, but it’s only an entry point. There are hundreds of classifications for files based on their attributes and purposes (i.e., business unit, country, privacy level and regulatory requirement). This need not be painful; in fact, it can be automated based on identified patterns in the file content or metadata fields.

Then there’s the action you need to take based on what you have — the decision you need to make. A common goal is to optimize the infrastructure in order to save operating expenses, as I’ve discussed, where culling valueless, “ROT” (redundant, obsolete, trivial) data typically results in a reduction of infrastructure and IT costs.

Knowing What Data You Have

Nonregulatory corporate governance decisions are highly existential. What data do you collect from users or customers? What do you do with it? How do you manage it?

A single transaction or social security number may be copied and moved hundreds of times and accessible to hundreds or thousands of employees. Your data governance policies must address information integrity, security and availability — but first, you must know what you have.

Future-leaning apps such as predictive analytics, modeling and machine learning require a clean data set to provide insight into the future of the business. I guarantee there are applications that have yet to be invented and commercialized that will access and reuse your data. You can’t leverage your data for these purposes and take action if you don’t have data control. So, in this case, you are ignoring an untapped revenue stream and have less knowledge about your business than your competitors have on theirs.

So, where does one start? What options or steps should a corporation take to gain data control as well as insight?

There are certainly very specialized vendors offering services around specific applications, for example email capture, index and archive to meet a financial broker-dealer regulatory need and these can work well. However, the reality is that data is fragmented and continually shared every minute. For some, deploying three to four different applications and signing up for external services can work; however, this introduces new layers of complexity, huge costs and limited interoperability.

Consider the following:

1. Look across your company at the applications and users that are generating data. Look at document workflow, including how it is created, stored and shared. 

2. Understand your user’s data behavior, including data sharing or movement.

3. Map out the demands of data, both short- and long-term, including any regulatory requirements as there are penalties if not addressed. 

With these basic three steps, you should be in a position to research solutions for your data ecosystem.

Solution Considerations 

You know your data is everywhere, so consider solutions that can traverse distributed data repositories to find and understand your data then easily classify without major resources. The infrastructure should enable you to act on your data, including moving, copying and deleting, but certainly not locking you into propriety repositories. Lastly, ensure that open and secure access to the captured data is possible to fuel your future-leaning apps.

Final Thoughts

As Sir Francis Bacon and Thomas Jefferson are both attributed to having said, “Knowledge is power.” Intelligent decisions stem from the ability to discover, classify, optimize and exploit your data. That key first step is finding. Finding and knowing its state, placement and availability is the first step to effective data control, compliance, cost savings and reduced complexity. It’s the first step to making the right existential business decisions.

Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?

Source Article