From small businesses to large enterprises, many organizations are coming to the realization that future business success relies on modernizing their data management approach and transforming legacy ETL implementations into modern data pipeline architectures.

Demands and challenges brought on by business forces, such as the deployment of a new AI tool or a corporate merger, are increasing the pressure on a challenging and sometimes misunderstood topic: data integration. The expectation of speed creates even more need for an agile perspective on deploying new data tools, and then data testing strategies, data accuracy, data lineage and security.

The Emergence of Modern Data Pipeline Architecture

Just a few short years ago, the common belief was that realizing these ambitions would require a significant and expensive overhaul of your entire data ecosystem, often in coordination with unreliable and complex ETL processes. If these ETL processes work (frequently they don’t), they actually lock down data in a predetermined state in Data Warehouses, rather than leaving it closer to its original state in Data Lakes and letting data-enabled business teams consume, analyze, and transform the data differently based on business needs.

Thankfully, most organizations are beginning to realize that the traditional ETL data transformation approach is not sustainable in today’s data environment. By using a modern data management approach focusing on simpler data pipeline architectures, businesses can quickly adapt to a variety of business pressures so that adding new systems and technologies becomes routine, if not downright easy.

Inflection Points: When Does Your Organization Needs to Modernize Its Data Platform?

If your organization is dealing with any of these modern data challenges, you may want to consider standardizing your ecosystem and speeding up installations with data integration solutions like the Enzo Unified Integration Platform.

• Executing Mergers and Acquisitions
• Leveraging Artificial Intelligence or Machine Learning
• Extending Legacy Software with SaaS Platforms
• Managing Multiple Remote Sites and Field Teams
• Implementing Cloud Analytics
• Leveraging Modern Cloud-Based Reporting Platforms, such as Power BI
• Building Data Lakes including Azure Fabric and Snowflake

Solving Complex Data Management Problems

All of these scenarios have one thing in common: they are inherently very difficult problems to solve without using the right tools. An AI model with insufficient data can lead to inaccurate forecasts and costly decisions. A merger that requires double the work to support two ERP systems will significantly change the value calculus of that transaction.

Modern data management teams must frequently deal with complex challenges, such as:

Diverse Data Formats – With so many file types and data formats in existence, unifying data can become inherently difficult. We’re no longer talking about just dealing with structured and unstructured data. Some industries have data needs that are heavily reliant on certain file formats. Emerging formats, such as Parquet for structured data, JSON for native web development and SCADA for IoT management, pose additional challenges. If your industry-specific ERP platform uses one format, and the hot new BI tool you just made an investment in uses another, getting all your data to “sing and dance” together takes some additional work. And that additional work will be needed every time you add a new data source, SaaS service or platform

With Enzo Unified, every file type, language and format is automatically standardized for you, and can be managed with simple SQL or HTTP commands.

Data Quality – When you consider that data quality issues cost the US economy approximately $3.1 Trillion every year, clearly data accuracy and quality is a place you don’t want your technology team to scrimp on. It’s also evident that initial data mapping and subsequent tracking of data updates is critical as you build your data infrastructure.

The Enzo Platform offers robust change data capture (CDC) technology built-in, making tracking and testing much easier. In addition, our proven installation process for the Enzo Platform offers a meticulous data mapping approach for greater accuracy out of the box.

Data Growth – As your business grows, and you need to incorporate more data sources over time, managing increasingly large datasets can be cumbersome and costly. Processing time can consume energy and resources, and delays can significantly impact service and product delivery.

The Enzo Platform offers both API abstraction and built-in High Watermark tracking enabling more efficient data processing times and significantly shorter implementations.

Evolving Business Requirements – It’s an old industry joke, at this point, but the reality is that business requirements are constantly being updated, and new solutions are needed all the time. As business stakeholders see more use cases, demand grows for data distribution to more endpoints. For example, perhaps you take the first step by integrating your ERP, such as Great Plains or Acumatica, with financial management software, such as Medius or Business Central. This increases productivity for the accounting staff right away. But now, the finance team wants to use this powerful data connection for greater business intelligence with tools such as Power BI or Tableau. Updating integrations to address new business rules, software releases or completely new data solutions would be an ongoing challenge within a custom-coded environment. It’s simply no longer acceptable to have a cumbersome integration process that takes three months to bring new software online.

The Enzo Unified platform makes individual software and SaaS updates easy, sometimes even a same-day endeavor. For brand-new software integrations, Enzo can have data flowing in less than 4 weeks in most cases. Additionally, because Enzo products were built using low-code and no-code interfaces, most “regular” updates can be completed in-house using SQL or HTTP code on the Enzo Platform or using a point-and-click interface on DataZen.

How a Data Integration Platform Can Improve Your Pipeline Architecture and Speed Up New Deployments

In today’s business environment, data teams can no longer afford a one-off integration every single time they want to make an update. Purpose-built integration solutions tend to turn into technical debt since they are isolated from most development upgrade cycles and can become less secure over time. In addition, these one-off integration solutions are usually point-to-point in nature which limits an organization’s ability to evolve quickly as new business integration requirements emerge. By standardizing your data integration process and implementing a common data integration platform that focuses on data pipelines and data abstraction, you can stop worrying about “the how” and start reaping the rewards of increased speed to market.

See how Odom Corporation, one of the largest beverage distribution companies in the US, is using the Enzo Unified Platform to standardize data integrations and create more efficiency.

>> Check out the Case Study.