How to solve your biggest SAP ERP data integration challenges

Stop struggling with SAP ERP data integration issues and easily connect and access your data in real-time using high-volume data replication.
July 7, 2022

It might shock you to discover that 99 percent of companies struggle with data integration challenges. Moreover, 65 percent of companies also say that access to ERP data is difficult, according to a recent global survey of ERP professionals conducted by Dimensional Research and Fivetran.

In today’s data-driven world, not being able to access or integrate your SAP ERP data, which is some of your business’ most valuable data, is more than just inconvenient, it’s costly. In the same survey, companies admitted that data challenges have caused them to delay decision-making (71 percent) and data analysis (69 percent). They also acknowledged that they had seen an impact to their core business processes due to data access and integration challenges.

What’s making it so difficult for companies to integrate their SAP ERP data and gain real-time access? Here are the top SAP ERP data challenges standing in organizations' way.

Challenge #1: Limited access to real-time data

The lack of access to SAP ERP data can directly impact your business—causing slowed operations, poor decision-making and even lost revenue. Yet, most organizations continue to struggle to gain quick access to SAP ERP data.

Source: Dimensional Research and Fivetran

The high volume of data stored in SAP systems, the speed at which new data is generated and the variety of diverse data formats and sources make it challenging to gain real-time access. But access isn't the only problem—managing the volatility at which data is available for consumption and connecting SAP ERP data to big data in order to extract insights is also hampering companies' ability to deliver real-time insights to business users.

The world of data is evolving, and the pace of data generation is accelerating. With the increase in the use of mobile devices, social media and interactive business processes, organizations are faced with unprecedented and crippling complexity. This is especially true when it comes to integrating SAP ERP data with other business functions, such as CRM, sales and unstructured sources (social media, streaming, etc.) to create a unified data view that can unlock the true potential of their combined data.

For example, to get actionable intelligence from online transactional processing (OLTP) data using online analytical processing (OLAP), data must be extracted, transformed, and loaded into a data warehouse for analysis. But OLTP and OLAP systems are siloed, making it difficult to access/extract/load for new use cases.

Historically, best practices dictated that OLTP and OLAP be kept out of sync. The data was batch loaded daily or monthly to analytical systems using in-house data pipeline builds and manual processes, such as file loading systems that may update daily, weekly or monthly. While this process gives business users access to the SAP ERP data, the data is stale.

Maximizing SAP ERP data with high-volume data replication


Challenge #2: Unable to seamlessly integrate SAP ERP data

A holistic view of your enterprise data assets is a key component of making smart business decisions. Yet, the challenge for organizations has been getting access to SAP ERP data at the speed and scale required while keeping costs reasonable.

Data integration challenges were listed by 51 percent of ERP professionals as a top hurdle in leveraging ERP data to achieve business goals.

While SAP ERP data has traditionally been accessed via data exports meant for single-purpose use, the business landscape is rapidly evolving. It's becoming more necessary and critical to scale huge amounts of enterprise data at speed.

Many organizations are building data pipelines in-house to manage data integrations, but it's nearly impossible to keep up with the evolving data climate. New product lines and new data sets are constantly being introduced, requiring data teams to continually rebuild their data pipelines. 

In fact, 48 percent of ERP professionals say their organization plans on adding 10 or more data sources over the next 18 months.

Challenge #3: Inability to operationalize SAP ERP data to maximize value

ERP professionals indicate that access to real-time ERP data provides significant advantages with faster decision-making, increased efficiency, improved accuracy, early problem detection and smoother operations. Yet, most organizations aren't able to operationalize their SAP ERP data to achieve these benefits.

Some of the challenges holding organizations back include:

  • Distributed enterprise landscapes that span cloud and on-premise: The complexity across environments often hampers companies from being able to gain maximum value from their SAP ERP data.
  • A lack of skilled resources to develop DIY data pipelines: Without the right in-house resources, companies cannot operationalize their SAP ERP data fully.
  • A need for robust security and privacy features: Security concerns keep many companies from being able to operationalize their SAP ERP data.
Source: Dimensional Research and Fivetran

Why use log-based change data capture (CDC) 

To gain maximum value from your SAP ERP data, you need to be able to scale your data pipelines to support ever-increasing volumes of transactional data as well as integrate SAP ERP data with structured data from sales and marketing as well as unstructured data from social media and sensor data to unlock business value in real-time.

The best and most cost-efficient way to achieve this goal is through high-volume data replication that uses log-based change data capture (CDC) technology. Log-based CDC is considered a superior replication method because it is able to handle large volumes of data at speed with minimal impact to transactional sources. 

The biggest benefit of log-based change data capture is the asynchronous nature of  CDC — changes are captured independent of the source application performing the changes.

Additional benefits include: 

  • Minimal source impact: Log-based CDC captures changes and moves only the changed data with minimal source systems impact
  • Fast performance: Directly reads the logs on the file system allowing highly efficient change data capture, supporting large volumes of data
  • More flexibility: Log-based CDC capture supports more data operations such as truncates and enables support for DDL capture 

How Fivetran’s high-volume data replication solves SAP ERP data integration challenges

Fivetran offers a best-in-class high-volume data replication solution with log-based change data capture (CDC). Whether you are on the latest S/4HANA implementation, a long-time ECC deployment or using non-HANA database technology, Fivetran can help. 

After initial data load, Fivetran’s log-based data replication technology identifies record modifications, such as inserts, updates and deletes, from the database transaction log and then asynchronously captures changes from the transaction log for downstream replication into the target source, such as a cloud-based platform. Support for special SAP structures and data types such as cluster, pool and long-text tables are made transparent for use in the target source. As a result, you have the ability to replicate CDS and calculations views to the target at ease. This process occurs in real-time without impacting SAP ERP data processing. Changes are efficiently micro-batched, resulting in a continuous flow of data with very low latency.

High-volume data replication continuously integrates SAP ERP data to support various technical use cases. Scenarios include, but not limited to: 

In conclusion, Fivetran allows you to automate high-volume SAP ERP data movement with minimal impact on transactional systems and near-zero latency to various cloud-based platforms. Our simplified, easy-to-use solution enables your data teams to spend minimal effort building and managing data pipelines and more time improving business decisions. 

Maximizing SAP ERP data with high-volume data replication


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