Why Data Is Like Chocolate

Data is often granted metaphors. People like to suggest that data is the new coal, the new fuel for modern business, or perhaps even the new snake oil i.e. a cure-all elixir that can transform and transport any organization to the new age of cloud-native, mobile-enabled, information-enriched business.

But perhaps data is also like chocolate.

1 – Some is light, some is dark

Some chocolate is milky, some is white and some is much darker. While modern artisan chocolatiers like to offer products with up to 97% cocoa solids and mark these out as their finest and usually most expensive products, dark data on the other hand is far less appealing.

Analyst house Gartner defines dark data as the information assets organizations collect, process and store during regular business activities, but generally fail to use for other purposes (for example, analytics, business relationships and direct monetizing).

2 – Over time, it goes stale

As most of us know, chocolate eventually turns stale if you keep it long enough. Scientists have said that this is due to a process known as ‘fat bloom’, where liquid fats such as cocoa butter crystalize on the surface. The reason most us find chunks of old stale chocolate at home is that people tend to ‘squirrel away’ some of our candy treats in drawers, in the fridge and in our handbags and manbags. Wouldn’t it be more sensible if we had a central chocolate tin that everyone (with appropriate privileges) could access when they needed?

“In this respect, we can see the choc-to-data parallel quite clearly. Certainly for data, it is far more preferable that we have one central place where it all resides. In that central location (be it data or chocolate) we can then tabs on where it is, how much we have at any moment in time, who has access to it… and (in the context of this point) know when it was out of date,” said Andrew Fitzgerald, sales director for Western Europe and Sub-Saharan Africa at Cohesity.

“Put in the context of data, stale chocolate occurs when your data is in siloes attached to legacy servers, databases, residing with developer teams using copies IT hasn’t known about… and in outdated backups. Organizations in this predicament have what we like to call mass data fragmentation. If you don’t get this resolved, you cannot reduce the total cost of ownership attached to data and infrastructure. Plus also, there’s no guarantee you won’t end up wolfing down an out of date Mars bar in a data emergency that ultimately ends up making you feel sick,” added Fitzgerald.

3 – It can carry hidden value inside

Like a liqueur filled chocolate, data can carry a hidden payload that offers more than its exterior might initially suggest. An example of this is the data created by customer facing applications and related cloud infrastructure. This carries more than a single signal and can be useful across different parts of the business.

“Your developers create new log data all the time and they use this data to see how well their applications are performing and how they are behaving with regards to requirements. However, this data can also be used for a business purpose too in order to provide information on business outcomes. Looked at properly, this data can help you understand what mix of customers you have, where customers are coming from, how much revenue your app generates per unit of time, at which times of the day and so on. We call this process continuous intelligence,” said Bruno Kurtic, co-founder at Sumo Logic.

4 – Some is uniform, some is  a ‘rocky road

VP of developer relations at DataStax Patrick McFadin says that today, in tech, whatever the question is, the answer seems to be more data. He suggests that if a business wants to make its customer experience more successful – then it needs more data. If that same business want to improve its lower level software development practices – then (no prizes for guess) it needs more data. But he warns, with more data there is a high probability that it comes with more data management headaches. Some solutions get needlessly complex with different technology to manage the scale issues all glued together… and you end up with rocky road chocolate.

“But, hard core data engineers love the kind of variety that you get with rocky road. For the majority of application developers and smaller organisations, picking rocky road may look like a great way to get a blog on Hacker News [i.e. kudos among the pro-geek community], but in business, practical engineering always wins. Looking at options for Database-as-a-Service (DBaaS) should be a no-brainer. You can rely on someone else’s experience and expertise to get you where you want to go. It’s a smoother approach to get started for new developers… and it keeps experienced developers building valuable code, instead of tending complex infrastructure and crunching through the choc-nut mixture,” said McFadin.

DataStax’s developer man points out that some teams may have big investments in data engineering already, they just want help in managing what they have. Using AIOps – where decisions and recommendations can be made automatically – is the next exciting wave of data engineering. As data infrastructure becomes more complex, we can have our rocky road, but in the mouth, it’ll feel like we’re eating smooth praline.

5 – It comes in a tin, for sharing

Data, like chocolate, comes in a tin. Or if not a tin, then it comes in a packet or container (in the form of a software application or database) that is responsible for its outer packaging and protection. This means that someone has to be responsible enough to look after the tin and make sure that enough sharing goes on.

As there is no single person, organization or entity responsible for the global data chocolate box, we are now seeing the rise of data marketplaces where data can be orchestrated, exchanged (bought or sold) and made available to others in various different forms.

A good example of this is Dawex, the company provides a backbone technology for enterprise organizations to create their own data exchanges where they can host a mix of internal and external data sources… and, subsequently, make those data marketplaces available to both internal and external stakeholders. Dawex doesn’t own the chocolate itself, but, in this case, it can provide the tin and a means for the right people to get a piece.

6 – Too much of it makes you sick

As anyone who has ever over indulged knows, too much chocolate makes you sick. While we think we might want that extra cube, chunk or even bar, there is a point at which enough is enough. So does the same go for data?

Global CTO at Tibco Software Nelson Petracek says that the ingestion process (for data… and for chocolate) does indeed have an impact. He says that a glut of data (especially low-quality data) can be particularly nausea-inducing and it can leave an enterprise feeling distinctly queasy and unable to focus.

“Large amounts of low-quality data only leads to negative outcomes, resulting in an organization that is lethargic, slow to respond and unable to move quickly – and (for want of candy-analogy) also fairly bloated and sluggish. This leads to a business that is distracted from what is occurring in the surrounding environment, which is obviously rarely a good idea,” said Petracek.

Advising that we need to think about how much data we’ve ingested and how much we’ve got in stock at any given moment in time, the Tibco CTO insists it is important to understand the sources and provenance of data in our inventory.

“Any steps that can be taken to improve the sources or associated processes for consumption should be carried out. We must also realize that it’s not just about quantity, but also quality. Focus on ensuring whatever you ingest is manageable and consumable by all interested parties, as this will lead to the most enjoyment and value. Whether it is data or chocolate, more is not always better,” said Petracek.

7 – Some is gourmet (enhanced & enriched)

As data optimization company Blue Sheep notes here on the subject of data enrichment, some data can be given the gourmet treatment to elevate it to a new level of service.

“Although not a requirement to cleansing, data enhancement can be very useful to add extra information to your records once they have been cleaned. For example, data can be appended with demographic characteristics, behavioural data, financial characteristics or property characteristics to enrich existing customer records and help marketers derive valuable insight,” wrote the company blog team.

So data, like chocolate, comes in many shapes and sizes, many different wrappings and packages… and is presented with many different flavors, fillings and fanciness. Some of it is even quite ephemeral, so make sure your business gets hold of the data it needs before it melts in your mouth.



Original post: https://www.forbes.com/sites/adrianbridgwater/2020/07/03/why-data-is-like-chocolate/

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