Unveiling the Advantages of No-Code and Low-Code Approaches for Data Extraction Workflows

A typical business day is loaded with data. And not just data coming into the formal pipelines. There’s data from everywhere. There’s structured data. There’s unstructured data. There’s raw data. There’s too much data. There’s foggy data. There’s warm data. There’s too cold-to-find data.

Yes – today, data is a constant problem and an opportunity for a business. But the people who actually deal with it are the people who have to handle data extraction for retrieving and consolidating data from multiple sources. They have to do it to fill some buckets and make some business decisions. The data extraction must be error-free, fast, and consistent so that this person can apply business intelligence and make it amenable for business purposes. This person usually sits many desks away from the guy who handles data extraction software. Perhaps, this is why we now hear so much about the emergence of low-code and no-code development in data extraction.

Low-code and no-code data extraction – the last-mile flip

According to Gartner, the worldwide market for low-code development technologies will have hit $26.9 billion in 2023, with Low-code application platforms (LCAPs) as the most significant component of the low-code development technology market (touching nearly $10 billion in 2023). By 2026, developers outside formal IT departments will make for at least 80 percent of the user base for low-code development tools, up from 60 percent in 2021. Also, the spending on hyper-automation-enabling software technologies would be as big as $720 billion in 2023. A growing number of enterprise-wide hyper-automation and composable business initiatives would be the primary driver for accelerating the adoption of low-code technologies through 2026.

Why would all this happen? Simple. Because the people who actually use a thing know how best that thing should work. They bet on low-code development tools’ intuition, flexibility, and composability. This is why there is a rise in business technologists and citizen technologists. They need lightweight solutions that fit closely with their functional business unit needs. They need technology to understand what they truly want – and empower them with enhanced productivity, efficiency, and agility.

A no-code and low-code approach works like a magic bullet here. In such a scenario, there is no need for a technical person to create the solution. The business user can himself/herself create the answer that s/he wants. With minimal to negligible coding needs, a user can put together a solution that truly understands the pain points of on-ground work. These approaches empower business users with real agility, reduced interruptions, and high productivity. In a no-code scenario, a user needs almost no coding work to be done because the platform is built-in with the necessary technical guts. In a low-code scenario, there is minimal work on coding to be done – which is possible easily through ready-to-use and UI-friendly components. With this power, non-technical users can create applications without going through the big application development cycle. The long and repetitive pipeline of requirement gathering, preliminary design, coding, testing, re-coding, and deployment gets crunched into a quick-to-use low-code tool. In fact, with no-code and low-code, data extraction takes a new form.

• It becomes quick – and devoid of bumps due to redundant process issues.
• It talks directly to the users of data extraction- with no translation loss between what the user wanted and what the coder gave.
• It becomes closely aligned with real analytics needs.
• It becomes accurate, contextual, and easy to correct – on-the-fly.

Considerations and best practices

For low-code or no-code data extraction to work all these wonders, it is essential to adhere to some tenets:

1. Identify the right use cases for no-code and low-code approaches – do not just slap anything on; make sure that the environment really calls for an abridged coding solution.
2. Evaluating the security and data privacy aspects – shadow IT can easily rear its head, leading to errors and threat vulnerabilities if low-code data extraction is not based on tight security frameworks.
3. Induce collaboration between business users and IT teams for successful implementation – low-code data extraction does not mean that IT expertise is sidelined completely. The best solution comes when both heads meet and find the power of symbiosis of business context and IT’s edge.

Challenges and Mitigation Strategies

A lot of low-code revolutions fail to take off from the ground. They falter due to some basic pitfalls:

• Fixing symptoms without addressing fundamental problems of inefficiency
• Hoping aimlessly to use a new tech without understanding its proper context and implementation approach
• The proliferation of too many low-code data extraction areas
• Unrestrained and poorly-monitored citizen coding- with another problem of fragmented IT 

To address potential challenges and limitations of no-code and low-code data extraction approaches, an organization should take the help of real experts. It is better to ask specialists for strategies to overcome these challenges proactively. The right platform helps you design and test a low-code data extraction in a way that fits your space and need.

Yes, low-code data extraction can propel your business users with a staggering speed and power in their business decisions. But it’s better to explore and adopt these approaches for improved efficiency and productivity with the right tools. Empower your non-technical users in the data extraction process. Let them find a typical day where they see- Wow! That’s data I can quickly and powerfully put into action! Learn how experts from Carvewing can help you in this direction.