Best Practices for Big Data

The promise of Big Data is massive — it can aid in research to help cure diseases, predict optimal sites to harness sustainable energy, forecast the ups and downs of the global economy, and tell us about our customers’ lives, preferences, and likelihood of buying, even before they know of it. 

Big Data will give you the answers to questions you haven’t even thought of yet. However, Big Data remains a challenging initiative for an organization to take on. You have to consider the cost of buying the technology to collect and process data, of the storage capacity where you will store massive amounts of data, and of acquiring or outsourcing the skills needed for Big Data. Then there’s security, compliance, quality, and more.

In Stratpoint’s years as a data services provider, we have experienced both successes and challenges. Big Data is a worthwhile — albeit complex — initiative. Thus, it is important to take into account these 6 Best Practices when launching your organization’s Big Data project. 

 

01 Big data is mainly about business, not just tech

It’s easy to get carried away by flashy new features that tech companies come up with on the regular. For example: real-time analytics. With real-time analytics, you can respond to what your customers are saying right here, right now. The technology is certainly available to do so. Besides, who wouldn’t benefit from real-time analytics?

Well, the first question you need to ask is: is the business capable of taking relevant and meaningful action in real-time? If not, then your team will be bombarded with data that it cannot process and make use of anyway. That just leaves you with money spent on the implementation and maintenance of technology that you are not able to maximize. 

Consider what the business needs — and not just take a ride with the latest technology. In this case, perhaps right-time analytics is a more worthwhile initiative than real-time analytics. 

 

02 Don’t be overwhelmed by the amount of data

Collecting and storing data from point-of-sale, IoT devices, social, website, third-party research agencies, among other sources, can be overwhelming. It’s understandable to think that your data scientists will have no use for all the data at this point in time, so why collect it? And you will be partly right.

Indeed, you should listen to the business and only handle and analyze data that you can manage, make sense of, and take action on. But do not be scared by the massive amount of data that will bring massive amounts of potential later on.

If you think it’s not time to take on real-time analytics, that’s fine. But you should still consider collecting streaming data and storing it for future use. Later on, the historical data can prove useful in detecting patterns, anomalies, challenges, and opportunities. Analysis doesn’t even have to be solely the realm of data scientists — machine learning and AI can go through volumes and volumes of data and provide recommendations. Imagine what you can uncover 10 or 20 years from now. 

In your big data initiative, you don’t necessarily have to know what to do with all the stored data today. Analyze what you can, and save the rest for later.

03 Democratize discovery and analysis through visualization

Decoding data at a massive scale can already be to those with the technical expertise — even more so to non-technical users. But finance, marketing, sales, and management — though without coding skills — are the primary consumers of data insight, and they have the most at stake when it comes to interpreting it for their business. Thus, it is critical to use data visualization to put data discovery and analysis in the hands of those who need it. 

When all users, technical or non-technical, have the ability to see and understand data, your big data project will more urgently help aspects of your business that need it.

 

04 Store data in its native form

Today, when you store video, audio, images, content, transactions, and other records, you don’t necessarily know when, where, and how the data will be used. That’s okay — it is impossible to predict all use cases and business requirements you will have in the future. Not to mention the technology that will someday be available to unlock the secrets of both your structured and unstructured data.

It’s a good thing that big data platforms allow for keeping everything in its native state upon storage. This way, you can wield the piece of information as you need it — and as technology will allow it — in the future.

 

05 Go Cloud

When you start storing all your data today, it will only keep growing next year, 5 years from now, 20 years from now. The cost of storage, backup, disaster recovery, high availability, security, and performance optimization for growing data can get expensive when maintained in physical servers, in your own data center, and by your own engineers. On the other hand, Cloud providers price data storage at a more cost-effective rate at scale. Moreover, an experienced support team for both your Cloud and your data can be available on Day 1. 

 

06 Govern your data well

Compliance with the Data Privacy Act is a minimum requirement when capturing data for storage. Apart from making sure you have the regulatory consent for your data, it is crucial that every piece of information is cataloged, tagged, detailed, and secured. It seems like a pain to tick every compliance box for every piece of information you keep, but your data scientists and users will thank you later.

When your users are confident that they are exploring data that is legally compliant, they will feel more free to dig deep and uncover gems of information. Having governance policies in place helps users be more efficient as well in finding, interpreting, and processing data today and in the future.

 

Best practices for your best data

Without a well thought of strategy, the promise of big data remains just that — a promise. So before jumping into the deep waters of big data, make sure you align your strategies with your IT, users, analysts, and management. If you need assistance in getting things rolling, Stratpoint can help. We have helped big brands and organizations deploy and use their data in the Cloud with success. Fill out the form below to set a meeting.

 

Source: Tech Target

June 27, 2022

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