The challenge of data collection

Business Intelligence (BI) and analytics tools are an essential part of digital transformation for every department of a business, from finance, marketing and sales to operations and HR. But, before they can offer any value at all, the IT department needs to be confident that these tools can access all relevant data, no matter what it is, or where it is.

Data collection and unification

Sales data might exist in CRM systems or a set of Excel spreadsheets. HR may have started using a SaaS HRM tool, with all associated data secure in the cloud. ERP data may reside purely at a business’ manufacturing site, inaccessible to other teams at other locations.

Coming from another angle, if a company has worked through an acquisition, it’s very likely that the acquired assets include one or more business applications with databases of legacy data that the operations team know contains value and insight that needs to be unlocked. The possibilities are as endless and varied as there are different types of business, staff and working practices.

What type of data is being considered and where and how it is stored are clearly key considerations. And they bring with them another, parallel challenge. On what sort of platform does your data reside?

Just as a business might have a set of disparate ERP systems, it might have a disparate set of data locations: either cloud, on-premise or hybrids of the two.

Suffice to say that locating, accessing and unifying your data ready for analysis is a challenge that scales not only with the amount of data itself but where it is, on what platform and in what format. So how should this challenge be tackled?

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Automated data unification

A business with just one or two data sources comprising just a handful or records could possibly develop a manual or whiteboard-based approach to data collection and unification. But as soon as those numbers increase any further — which is the reality for just about every mid-size organization — then a whiteboard, or even manual labor-based approach, should be parked for good.

It’s at this stage — with businesses most likely working with multiple data sources comprising thousands or hundreds of thousands of records each that an automated, software-based approach is required.

Bloomberg would be the first to agree. Rule number two in their Four Rules for Achieving Scalable Data Unification study is clear: “scalable data unification systems must be mostly automated.”

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Automated data automation benefits

The key word here is automated. Not least because businesses often fail to unlock any value from their data as they find the task of locating, accessing, collecting and unifying the content in source databases so much of a challenge that they just don’t bother at all. Or, they might tackle some data sources but intentionally overlook more technically complex ones.

Another reason to automate is that, if the job is being done at all, then it might very well be being done manually. But a hand-made, DIY approach to data collection is riddled with potential pitfalls, not least human error, time and financial costs.

Thinking more broadly, a sophisticated, automated and scalable system of data collection and unification is not just the first key challenge in becoming a successful, data driven organization. It’s also a fundamental tenet of sound business practice. The process of understanding and managing what data you have and where is the bedrock of corporate and information security, data governance and corporate best practice.

The Register’s sister publication, The Next Platform would agree. “An enterprise without a good understanding of what data they have and where that data is,” they explain, “runs the risk of corporate data going out the door and having no way of knowing that the data is lost or stolen.”

Businesses often fail to unlock any value from their data as they find the task of locating, accessing, collecting and unifying the content in source databases so much of a challenge that they just don’t bother at all. Or, they might tackle some data sources but intentionally overlook more technically complex ones.

ZAP Data Hub tackles the challenge of data collection and unification and takes the recommended, automated approach. Read more about how ZAP Data Hub provides automated data collection from apps and data sources of any type. This delivers high-speed, stable data migration for even the largest and most complex data silos, resulting in major financial savings while mitigating risk associated with proprietary and manual data preparation.

IDC White Paper

Enterprise‐Grade Data Management

for Midsize Organizations

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