20 Minute

Complimentary DAM Assessment

Michael Coorey
By Michael Coorey on Jun 23, 2020 11:06 AM

Solving modern business challenges with Data Integration

Data integration comes in two different categories, depending on your definition of “data integration”.

The traditional definition of data integration is something along the lines of “... the process of combining data from two or more sources to provide a unified view.” -  with the intent of extracting business intelligence, by viewing consolidated reporting or performing data analysis to draw out insights.

A modern definition of data integration is “...creating a flow of data and information between applications, at the speed of business” - to improve customer experience; increase revenue; reduce time-to-market; or lift employee experience and productivity. If you are in the Defence, Security, Health or Medical space, data integration will even help you detect threats in real time and save lives.

The introduction of SaaS for specific point solutions - such as CRM, or Invoicing - has also introduced siloed information repositories, which then bring rise to a new set of problems that the old monolithic era did not have.

With a correct operating definition, your data challenges can be identified before they prevent you from achieving control over your processes and your output.

To prevent stagnation in your business, meet the needs of your customers, and gain value from your application, processes, and functions, you need data integration.


Data stuck in silos

You have customer data scattered across various applications. Your departments are not communicating. You have outdated data, new data, and some that you cannot even tell if it is relevant. You are dealing with the problems of data silos.

What is a data silo? And how did they come to cause such disruption in your business?

A data silo occurs when information is only accessible by one department of your company. They might have occurred because different departments might not leverage the same apps. Two people, from two different departments, may have created databases to log the same kind of information and never investigated whether one already existed.

Some common problems encountered include:

  1. Reduced visibility of your data - there will be no clear way for you to create data-driven insights.
  2. No collaboration - your teams work independently instead of with each other.
  3. Reduce good customer experience - you will have a fragmented view of the customer journey and be unable to improve customer experience.
  4. Low data accuracy - because you cannot tell how recent your data is, you cannot guarantee its accuracy.

You may be thinking that this looks pretty grim. So, how can you fix it? 

There is no need for panic, just a good data integration platform, or the right data integrations-as-a-service.

If you store data across various systems, you can integrate those systems, resulting in collated and up-to-date data across your entire company.

Imagine that when a customer updates their details, all of your systems receive that updated information, for you to access whenever you need it. For your customers, they can experience improved customer experience and the confidence that their information is ready anywhere and anytime they interact with one of their services.

While data integration will resolve the technological silos within your company, it cannot fix communication barriers. To further prevent siloed data in future, you must establish lines of communication to connect the various departments. 


Data lost in translation

Effective communication between your technical and business teams is imperative when sharing data. You need to establish a shared vocabulary of data definitions and permissions.

Data governance and data stewardship can assist you in achieving this shared understanding.

  • Data governance — focuses on the policies and procedures surrounding your data strategy.
  • Data stewardship — a data steward, is someone that oversees and coordinates your strategy, and implements policies, aligning your IT department with your business strategists.

Data is critical to your company’s success, and the amount of data you create is likely growing. If you do not have a roadmap, misinformation and misalignment can arise in your integration processes.

It is necessary for you to carefully examine your business goals and needs and establish why it is essential to integrate and overcome any data integration challenges. If your team has a positive mindset and company culture, along with the necessary tools, you can overcome any data integration challenges you may face.


Disorganised data

Centralising your data is easier said than done, and disorganised data is usually the result of a company relying on people to manage it. Curating and combining data is time-consuming, especially with the vast amounts of data to create, gather, and manipulate; it is not hard for disorganisation to arise. A more valuable use of your employees’ time would be to analyse data insights and drive useful business practices.

If your data is unorganised, it can prevent you from making smart business decisions and negatively impact your marketing strategies. For this reason, it is helpful to leverage a smart data integration platform that completes the majority of the work for you, which gives you more time to concentrate on other areas of your company.


CF - Subheading Manual Data Collection

Manual data collection

Real-time data collection is imperative for specific processes. A retailer that owns an e-commerce site, for example, may want to display individual, targeted ads to each customer depending on their search history. Your team cannot meet these demands if they cannot collect the data quickly. Realistically you cannot rely on your employees to manually manage the data in real-time, not to mention that the majority of organisations do not have the resources or team capacity to attempt such a time-consuming task.

To scale the task of manual data collection, you need an automated data integration tool. With this, you can ingest data in real-time, resulting in innovative and reactive services. Technology like this gives you reliable, curated real-time data without sacrificing any of your resources.


Incorrect formatting

If you have inconsistent data that is disjointed or not formatted correctly, it is not actionable and therefore has no value. Manually formatting, validating and correcting the data is time-consuming, and like collecting it manually, there are other things your team could be focusing on.

Data transformation tools help you overcome this challenge. These tools analyse the original base language and then determine the correct formatted language, after which they automatically make the change. Not only does this process eliminate the stress of data integration, but it also reduces the number of errors, mainly because your data team can flag and inspect code anywhere in the transformation pipeline.


Low-quality data

The repercussions of poor-quality data can seep into every aspect of your company. Low-quality data can lead to customer dissatisfaction, increased operational costs, loss of revenue, missed insights, and reputational damage. For this reason, you need to ensure that you have a data quality management process.

To ensure you drive innovation, stay compliant, and make accurate business decisions, you need to validate your data immediately after ingestion. If your team can accomplish this, you significantly reduce the amount of poor-quality data in your systems. Monitoring your data pipelines for outliers is also worthwhile as you can automatically identify errors before they become complicated issues.


Duplicate data

Duplicate data can quickly become a severe problem for your company resulting in poor customer service, a loss of income, and lack of productivity. Over an extended period, duplicates can cause severe problems. More duplicates result in higher risk to your business.

If you have a ‘silo mentality’ problem in your company, duplicates can burgeon into a problem. If your team does not share and communicate data effectively, then your data integration pipeline quickly contains duplicates and unexplainable variations. 

You can prevent this by implementing the following:

  • Establish a data-sharing culture where you educate and train your team on how to handle data efficiently.
  • Standardise your validated data, ensuring everyone can understand the data.
  • Invest in communication technology that will bring your team closer.
  • Promote transparency and keep track of data lineage by maintaining regulatory reports.

You can avoid duplicates if you implement the right tools, processes, and knowledge throughout your team. When you have access to organised data, your marketing and sales teams can work together and increase their efficiency.

Creative Folks provides a range of technical services to assist you in planning, designing and implementing data integration. If you would like to know more about how we can help you overcome your data integration challenges, please get in touch with us.

Topics: system integration, data integration

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