5 Practical Tips to Modernize Your Data Integration

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Tech Insights for ProfessionalsThe latest thought leadership for IT pros

Tuesday, September 29, 2020

Are you making the most of your data? Here are a few key tips to help you bring your data integration solutions right up to date.

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5 Practical Tips to Modernize Your Data Integration
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The modern business is built on data. Indeed, according to the World Economic Forum, it's estimated that by 2025, the world will create around 463 exabytes of data every day - that’s the equivalent of 212,765,957 DVDs every 24 hours. Already, it notes that every day, 294 billion emails are sent, along with 500 million tweets.

How firms manage this deluge of data could well be the difference between success and failure. Those that are better able to collate, analyze and act on their information stand to reap major benefits, with figures from McKinsey showing that they’ll effectively generate 93% more profit than those that don't.

But the problem for many firms at the moment is their data is hard to access or in the wrong format to be effectively analyzed. Talend notes that more than half of business data isn't easily accessible, meaning up to 80% of a data analyst's time is spent simply finding and preparing data. When it comes to unstructured data such as media content, which often makes up the majority of a firm's data, just 1% is used at all.

So how do you improve this situation and ensure your data is fully integrated and available for use? Here are five things to do.

1. Ensure all your sources are connected

Today's data comes from a wide range of sources, so it's vital you're able to connect all of these to be successful. While traditional data sources, such as relational databases, Excel files and applications like Salesforce need to be taken into account, this is just the tip of the iceberg.

A modern data integration solution needs to be able to connect unstructured data such as audio and video, machine data from Internet of Things sensors, and gather from both cloud and on-premise services. Advanced extract, transform and load (ETL) solutions must also be able to work in real-time to turn this into useful information, rather than traditional overnight batch processing.

2. Focus on data quality

Having access to the right data won't do you any good if what you're collecting and integrating is outdated, inaccurate or replicated. This will lead to poor results when you try to derive useful insight from it - as the old saying goes, garbage in, garbage out.

Data cleansing to filter out these issues can be a highly tedious activity, so make it as easy as possible by doing as much as you can at the source, such as within your CRM and ERP systems. Standardizing data entry fields, running checks against external sources to compare for accuracy, and using deduplication software all helps ensure that when your data is collated into a central system, it's fit for purpose.

3. Embrace the cloud

Turning to cloud-based solutions for data storage and analysis can greatly help businesses take control of their data and ensure it’s integrated effectively. For starters, these tools offer easy scalability, which is vital if you're looking to build data lakes using very large datasets, while they also come with powerful big data analytics tools to help you make the most of it once it's there.

"Modern, comprehensive data integration can run anywhere - on premises or in the cloud - to liberate siloed systems to provide the business with the greatest data value. Data integration in the cloud enables developers to design unified solutions that can run natively for local performance or functionality advantages." - Philip Russom, senior director of data management, TDWI Research

 

4. Select the right integration tool

Specialized data integration tools can make the task of collating and modernizing data much easier, but there are a lot to choose from and they don't all offer the same functionality. Therefore, it's important to look closely at the options and identify what features are especially important for the business.

For starters, you'll need a solution that can access the entire breadth of your sources, both on-premise and in the cloud, and it should also be able to both read and write data in order to perform key transformation and cleansing processes such as:

  • Sorting
  • Filtering
  • Aggregating
  • Deduplication
  • Data matching

Features such as easy scalability and the ability to work across multiple providers are also important.

5. Keep things as simple as possible

Making sure that the data you collect is as simple and streamlined as possible is also vital. For instance, if you're collecting user details from an online form, ask yourself how much you really need. Restricting fields to just the minimum you need to identify and contact a person won't just make it easier to clean, load and add to your analysis tools, but will also make it simpler to stick to vital privacy regulations.

This also applies to your data integration and analytics solutions. Don't spend time overengineering complex solutions if it’s more important to deliver results quickly, or get distracted adding more functionalities that’ll slow the process down while only offering minimal value.

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