Data integration is essential for bringing your data pipelines together. But beware: it’s no easy feat.
Various data integration problems, such as connectivity, poor data quality, and lack of collaboration are very common. If these problems aren't dealt with properly, they could affect wider business processes, like business decision making and data accessibility.
Fortunately, CloverDX can overcome these problems, in turn allowing you to:
- Increase company-wide productivity and collaboration
- Solve the entirety of your data problems, not just the easy 80 percent
- Benefit from full automation and scrap tiresome manual processes
Tangible benefits like these make solving data integration problems an attractive proposition. With that in mind, here are four common data integration problems and how CloverDX solves them.
1. Data connectivity
When you consider how many databases, applications, messages or APIs you have – the challenge of integrating each set of data can seem insurmountable. Couple this with different data ‘gatekeepers’ loading and formatting the data in different ways, and the situation only becomes worse.
Ultimately, with haphazard data connectivity, you’ll fail to gather all of your data pipelines into a centralized location. This could lead to poor business insights, delayed data delivery, and a lack of data coherence.
So, how can you solve this data connectivity issue with CloverDX?
With our tool, you can overcome basic data connectivity issues, navigate complex data structures, and drive coherence through enterprise data mapping. CloverDX includes:
- Pre-built and well-optimized connectors
- The capability to work with a wide range of different data formats and delivery methods in a unified way
- The option to build your own unique connector from specific data sources
With the right tool, you can make sure your data is connected, integrated, and available on time, in one central place.
2. Data quality and validation
Did you know that 84 percent of CEOs are concerned about the quality of data they’re basing their decisions on?
Without high data quality, you’ll struggle to get the insights you need to make successful business decisions.
But data quality problems can affect more than just your future endeavours. These issues can also:
- Hinder productivity. When spotted, poor data quality requires the time of your teams to fix and validate any issues.
- Affect your cashflow. If faulty data delays your data-driven tasks and projects, you could face financial repercussions down the line.
- Cause compliance issues. In industries with many data regulations, you need to keep data quality at a high standard. Any slip-ups, and you could face reputational damage or fines.
Unfortunately, fixing and validating data manually isn’t always as easy as it might seem. When the scale’s so large, the task becomes costly, which increases the temptation to simply not do it at all.
CloverDX resolves this problem by automatically spotting and fixing outliers within your data. It also validates information as soon as it's ingested. This means data quality and validation is never an afterthought. The result? You reduce the need for manual intervention and you don’t lose money, time or your reputation down the line.
3. Collaboration between your teams
When it comes to data, tech teams and business teams need to work together to make your data integration processes seamless.
However, communication and collaboration isn’t always easy. Your business teams - who are more interested in the context (rather than the technical sides of things) - may not be able to translate their needs easily, and vice versa. Add various formats, variations of data and scale into the mix, and data integration becomes an even larger task for your developers.
To cut the time it takes to integrate your data, reduce the burden on your developers and ensure context isn’t lost along the way, you’ll need to rely upon a tool to do the hard work for you.
This is where CloverDX comes in.
Our data mapping and ‘bridging’ process ensures your business needs are never lost in translation. By turning pre-defined building blocks and templates into runnable code, your developers can quickly and iteratively integrate your data and create business-driven data models.
4. Data trust and auditing
Conducting regular data audits is an intrinsic part of staying compliant and ensuring your data is high quality. However, without knowing where your data is, you’ll struggle to understand where there’s room for improvement.
The potholes of poor data integration make the auditing process more difficult. With data residing in different silos, with different owners, it can be near-impossible to get a complete view of your data ecosystem. However, without this, you’ll never fully trust the quality of your data.
Automating your data integration process ensures that no stone goes unturned. No matter how complex your infrastructure is, CloverDX can pinpoint and integrate any dataset. From there, you can easily trace your steps and ensure your data is compliant with data regulations.
The CloverDX course of action
From communication difficulties to poor data quality and lack of audit-ability, there are numerous challenges to overcome when integrating your data manually.
Technology is the key to bettering your data integration processes. With our intuitive tool, your business can:
- Increase collaboration between your teams, in turn boosting productivity
- Overcome even the most challenging data problems
- Scrap error-prone manual processes in favor of full automation
This automation will free-up time for your technical teams, provide reliability, speed up your time-to-market, and ensure you’re always one step ahead of your competition.
Keen to find out more? Discover CloverDX for yourself with our 45-day free trial.
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