What to Know About No-code Data Pipelines for Data Warehouse Modernization
On October 2017, Chris Wanstrath, the co-founder and former CEO of GitHub said, “The future of coding is no coding at all.” And though it’s not an absolute reality today, no-code platforms have seen tremendous growth in the recent years. Forrester predicted that the no-code development platform market will grow to $21.2 billion by 2022. Are no-code or low-code data pipelines the way to go for your data warehouse modernization projects?
Here are a few considerations for when to choose a no- or low-code solution as opposed to hand coding data pipelines.
Understand the risks of hand coding
Organizations may think that hand-coding provides absolute freedom to customize a solution to their exact needs. And to be fair, hand coding might make sense for very simple, targeted projects that will not require a lot of maintenance or situations where there are no off-the-shelf solutions available.
However, many organizations lack clarity on the costs of data integration projects (see this recent Spotlight Report from Bloor on understanding the ROI of data integration tools). Problems with custom code begin to mount as integration requirements gradually grow. Custom solutions are neither scalable nor extensible due to multiple issues like lack of reusability, maintenance overload, and unavailability of the original developer. As a result, what started and seemed like a simple project often becomes a complex and costly affair than initially expected.
Key challenges with hand coding data management
- An expensive proposition – It may appear less costly in the beginning to get started. However, deploying to production, ongoing maintenance, and ability to accommodate changes is time consuming, risky, and expensive. In addition, hand coding data management for cloud deployments requires expert developers which are often hard to find and can be expensive.
- It’s not future-proof – The pace of change has increased exponentially – change in sources, change in ecosystems, change in execution engines, change in latency, change in business requirements, change in types of users. As soon as your hand-coded data integration is up and running, it’s obsolete, meaning you must continuously recode, retest, and re-deploy.
- It’s not scalable – Data volume is growing exponentially, new data types are getting introduced, and there are many more data consumers. There simply are too many data integration requests for hand-coders and developers to keep up. The only way to meet the needs of the business for more integrated and trusted data is through automation, and this requires AI and machine learning.
- Lacks breadth of modern data integration – It took many years for traditional data integration hand-coders to realize how important and necessary data quality and data governance were to ensure the business had trusted data. You need one unified user experience for data integration, data quality and metadata management (such as end-to-end detailed data lineage and more).
Hand-coding often doesn’t support the industrial strength that comes from a platform which has hardened over the years. Think of a platform that handles 15 trillion+ transactions every month or terabytes of processing in seconds or supports the most extensive industry standards and regulatory compliances like SOC2, SOC3, HIPAA, and U.S.-EU Privacy Shield and is aligned to international security standards such as ISO27000. For internal developers to harden your platform to this extent would either be impossible or at a minimum be extremely expensive.
Avoid the risk of custom coding: Adopt a modern, cloud-native approach
Today, more organizations are moving away from rigid hand coding practices. They are adopting integration solutions that are simple to use and operate, come with AI-ML driven intelligent productivity and automation tools, and can scale instantly up and down based on your business needs. With such tools you can reduce time to build your data pipelines from weeks/days to hours, with zero coding.
To accelerate and simplify your cloud modernization journey you need solutions that include three essential pillars built on a foundation of artificial intelligence and machine learning:
- Cloud-Native Data Integration – Intelligent, automated, cloud-native data integration capabilities—such as a codeless visual interface, prebuilt mappings, unified pane of glass for all users, and a serverless infrastructure.
- Cloud-Native Data Quality – An enterprise data governance program with intelligent, automated, cloud-native data quality ensures that the data in your cloud data warehouse and lake is clean, standardized, trusted, and secure.
- Cloud-Native Metadata Management – A common enterprise metadata foundation enables intelligent, automated, end-to-end workstreams across your data environment, facilitates collaboration, provides visibility into end-to-end data lineage, and promotes efficiencies.
3 examples of customer success with no-code data integration
With Informatica Intelligent Cloud Services, the industry’s leading cloud-native data management solution you can lower your TCO, reduce your risk, while being innovative, agile, and operating your business at high speed.
- Accelerating project delivery with lower total cost of ownership: A Russian commercial neobank based on Moscow took just one month to define project requirements, complete a pilot, and provide data for analysis because the graphical development, self-documentation and collaborative features of Informatica’s intelligent, automated, cloud-native data management solution. It enabled them to launch production-ready data pipelines up to five times more quickly than hand coding allowed.
- Meeting customer demands: A leading provider of last mile logistics services in North America was struggling with technical challenges that was impacting the onboarding process for customers and partners. To pull in customer order information and transform it into a format that worked with the organization’s core logistics system, engineers needed to custom code the specific parser routines. Hand coding was a cumbersome process that led to delays in bringing new customers on board. Informatica platform’s universal data transformation capability enabled the client to exchange and transform data in any format and from any source. And with the platform’s codeless, point-and-click development environment, the client is now able to avoid building rigid, custom-coded data parsers that tie up engineering resources and create costly delays.
- Accelerating cloud modernization: For a multinational law firm based in Australia hand coding was getting too difficult to maintain. Moreover, it wasn’t proving to be enough for their data integration, data quality, metadata management, and data governance efforts. Informatica helped them replace hand-code integrations, accelerate modernization to an AWS cloud data lake, and drive actionable insights.
To learn more, watch the video about reasons to choose a no-code data integration solution versus hand coding.