How to choose a No-Code Data Analytics Platform

No-code data analytics platforms are a new generation of software tools that enable businesses to analyze, visualize, and gain insights from their data without the need for coding skills. These platforms provide a more accessible, cost-effective, and flexible way to perform data analytics, making it possible for non-technical users to derive value from their data. As the popularity of data analytics continues to grow, no-code platforms are becoming an increasingly important tool for businesses looking to harness the power of their data.

By 2024, up to 65% of application development will be done on a no-code or low-code platform, according to a Gartner Magic Quadrant report. However, implementing these is proving expensive and time-consuming for enterprises Simply because there is not enough talent.

Visual tools without code play a significant role in bridging the gap for data scientists and making artificial intelligence accessible to non-technical or business users. With the use of these tools, companies can create datasets, train, and deploy models without requiring extensive coding knowledge. This process can be done in a shorter amount of time and at a lower cost. Additionally, these tools allow developers to be more creative with the data and models they wish to train, without the need for a Ph.D. in AI.

However, traditional data analytics platforms are often expensive, require specialized skills, and take a lot of time to set up. This has led to the emergence of no-code data analytics platforms, which offer a more accessible and cost-effective solution for businesses of all sizes.

What is a No-Code Data Analytics Platform?

A no-code data analytics platform is a software tool that enables non-technical users to integrate, analyze and visualize data without writing any code. These platforms use drag-and-drop interfaces, pre-built templates, and data connectors to allow users to build reports, dashboards, and other visualizations without any coding skills.

Contrary to popular belief, choosing a no-code data analytics platform solely based on its ease of use may not be the best approach. While ease of use is essential, it is not the only factor that should be considered.

It is important to note that no-code data analytics platforms may not offer the same level of flexibility and customization as their code-based counterparts. This lack of flexibility can limit the types of analyses you can perform and the insights you can gain from your data.

If the platform is not providing the same level of control and customization as traditional code-based platforms. This can limit the ability to fine-tune models, algorithms, and analysis techniques to meet specific business needs. Furthermore, no-code platforms may not be able to handle large datasets or complex analyses, which can limit their usefulness for businesses that require in-depth data analysis.

While no-code data analytics platforms have their advantages, it is important to consider other factors such as flexibility, customization, and the ability to handle large datasets and complex analyses. Ultimately, the decision should be based on a careful evaluation of your business needs and the platform’s capabilities.

Unpopular opinion about No code data analytics platforms

Another unpopular view of having a no-code data analytics platform is that it may not provide the same level of transparency and visibility into the data analysis process. Without the ability to view and edit the underlying code, it may be difficult for users to understand how the platform is processing and analyzing data.

This can lead to potential errors or biases that may go unnoticed, which can have significant implications for decision-making. Additionally, some argue that no-code platforms may not allow for the same level of collaboration and knowledge-sharing among data analysts, as it may be more challenging to share and discuss code-based solutions.

Developer’s Perspective:

Gartner and Forrester have released reports on low-code/no-code platforms, but understanding the nuances is crucial. Each platform targets specific audiences, such as business people, citizen developers, and traditional developers, and offers various types of applications. Categories range from Excel-like applications with advanced features to mobile and dashboard apps, and even basic applications that don’t require coding. With so many options, there are numerous best platforms in each category, each catering to different requirements.

the ideal platform must allow for unimpeded advanced development, support popular UI frameworks, operate on an open-source model, offer microservice support, enable immediate previews and deployment, provide team collaboration and version control, include no-code options for basic development, offer advanced access control, and support mobile UIs.

So, Unless you are a technology-focused company that requires coding, there may not be a significant need for code-based platforms. It’s not that coded platforms are inferior, but they can be time-consuming. On the other hand, no-code and low-code platforms enable you to create workspaces without writing code. These platforms are developed and maintained by coders who have already done the fundamental groundwork.

Why should you choose SCIKIQ as a No-Code Data Analytics Platform?

SCIKIQ is a non-binding, flexible, and scalable platform. It’s not a SAAS Application but this can be customized based on the data analytics need of the organizations. SCIKIQ is an advanced AI-powered business data platform designed for medium to large companies struggling with managing data across multiple systems, geographies, legal entities, and functions.

When it comes to choosing a No-Code Data Analytics Platform, there are a range of opinions on what factors should be considered. Some argue that prioritizing user-friendliness and visual appeal over technical capabilities, flexibility, and scalability is a mistake.

Others believe that No-Code Platforms are overhyped and cannot compete with traditional coding methods, limiting the ability to customize and create complex solutions. Still, others argue that No-Code Platforms are only suitable for basic analytics tasks and lack the necessary features for more advanced analysis.

Choosing a platform based solely on cost is also considered by some to be a mistake, with the cost weighed against benefits and long-term savings. Finally, the notion that popularity and market share should be the deciding factor in selecting a No-Code Platform is also challenged, with some suggesting that niche options may better fit specific use cases or offer unique features not found in mainstream choices.

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