In the technologically advanced world we live in, data overflow has become a significant challenge that many companies across industries such as manufacturing, oil and gas, and logistics are facing. Data overflow means that the system or systems that are holding your data can not compensate for the amount, thus causing visibility and reporting issues, to name a few. This can greatly affect many different areas of a business. This is specifically affecting SAP ERP customers and it’s become increasingly more important for them to find a solution to solve overflow challenges.
In an insightful webinar highlighting the common challenges surrounding data overflow, Pillir’s CEO Vaidya Aiyer and CRO JR Butler discuss how to cost effectively move SAP ERP data to a secure, modern, cloud-native data lake. Otherwise known as no code data ingestion, this process allows you to accurately report and analyze your data by moving it from external sources to one, easily accessible location. So how does EdgeReady Cloud support no code data ingestion and why should you consider our solutions? Watch the webinar video below to learn about no code data ingestion from SAP to cloud data lakes.
Business Case for Data Lakes
SAP is very different in the modernized world today and has increasingly added more applications to its catalogue. For this reason, data is scattered everywhere, making it difficult to understand the big picture. To understand why data ingestion from SAP to cloud data lakes is beneficial for SAP ERP customers, it’s first crucial to emphasize the different attributes of the business case for data lakes.
- Best of Breed: The best of breed environment refers to when your SAP is the digital core for your enterprise. In this environment, SAP customizations inevitably can lead to additional effort for new projects and maintenance, taking away valuable time from your team.
- Multiple Data Sources: Many corporations have their data located in multiple systems, various internal data sources such as sensors, devices, IoT, or external sources like web, Social or partner and customer sources.
- Big Data Analytics: some corporations also may be looking at big data analytics, such as all the cognitive and predictive modeling needs, machine learning application, and leveraging systems of innovation with hyperscalers.
- SAP Costs: SAP costs are a common pain point for many enterprises as it consists of SAP infrastructure costs, varied skill sets by members of your team to know the platform, along with high industry demand for people with these skill sets and low supply.
In this business case, it’s extremely valuable to consider no code data ingestion from SAP to data lakes. So why are many corporations reluctant to adopt this solution?
Challenges of Data Ingestion
Companies with data overflow struggle with not only the technical aspect of locating data and pulling it from SAP, but also the thought of the customizations or business tools that are also involved.
Below are some key challenges of data ingestion for SAP ERP customers:
- Data Access: SAP is largely built on Proprietary tools, languages, and APIs. Additionally, technical and functional SAP expertise is needed in order to maintain the data, and responsible access to the data should only be given, in order to not introduce security risks
- Complexity: Data preparation, data persistence and guaranteed delivery, data manipulation, and client-server models are just a few things SAP ERP customers are wary of when it comes to complexity in their systems.
- Cost Inhibitors: SAP infrastructure costs, human resource costs, and licensing models all contribute to the total cost of maintaining an SAP ERP system and trying to extract data out of it. Companies don’t want to have to spend millions of dollars on extracting and moving the data.
- Lack of Skills: Highly specialized skill sets are necessary for the data ingestion process, which you may not have within your company, costing you more to try to locate an expert externally.
In short, companies are aware of the fact that multiple data sources and customized systems not only generates more work but also drives up cost and slows down innovation.
Data Ingestion Solution for SAP
So how can companies effectively move SAP ERP data to a secure, modern, cloud-native data lake? There are four facets to adhere to when adopting this solution:
- Simple and Scalable: Data ingestion tools must be simple, so that anyone on your team can use them with minimal training, i.e. freeing up resources. It also must be scalable. With Pillir’s solutions, you can be sure that you’ll have cloud-native architecture, mission-critical infrastructure, no-code approach, and an easy-to-learn and deploy tool in place.
- Native Integration: Native integrations are important because SAP customizations are inevitable- every business process is unique and needs to be supported based on the needs of the business. This shouldn’t impose on the data ingestion process in order to move it to data lakes. EdgeReady Cloud offers just this- and natively integrates to SAP, discovers all customizations with no code and applies business rules in a streamlined fashion.
- Governance: Governance refers to data being persistent and easy to manipulate, while also offering reporting, management, and guaranteed data delivery.
- Affordable: If you’re thinking of moving to the cloud, it must be a consumption based model, with no upfront investments and is quick and easy to deploy.
No Code Data Ingestion for SAP with EdgeReady Cloud
EdgeReady Cloud is a useful data ingestion tool to consider when looking for a solution to extract your data and move into the cloud. By moving data to the Cloud, you can be sure that you’re cost effectively moving SAP ERP data to a secure, modern, cloud-native data lake.
EdgeReady Cloud is a no-code, rapid application development platform through which you can achieve data ingestion and also get real-time updates, data storage, data governance, data transformation all combined into one solution. Additionally, the drag n drop interface allows users to visually see what’s happening, pull the data, and modernize it easily.