The No-Code Snowflake Alternative for Business People

This article will discuss the rationale and benefits of democratizing data preparation and self-service with this Snowflake alternative.

With the advent of modern analytics, “data democratization and self-service” are now maxims for most Saas offerings we see in the data industry today.

In 2020, Gartner predicted that “50% of Organizations Will Experience Increased Collaboration Between Business and IT Teams by 2022”.

Safe to say, we’re living in that reality.

Data Democratization – The Why

Let’s look at the state of things happening in the data space today.

The Preamble.

1. Now more than ever, organizations are collecting an unprecedented amount and variety of data.
2. Source data is frequently decentralized and flows through pipelines where use cases govern its ingestion, storage, transformation, and distribution.
3. Analytics platforms are now more accessible to a wider audience to support decision-making.
4. Teams and people outside of IT (or without access to formal data prep processes) typically have to wait for another team to prepare their data. This causes users to extract data from systems and organize it in spreadsheets.

The Aftermath.

• Uncontrolled, inefficient stand-alone systems are created.
• Stand-alone systems quickly  lead to an abundance of data silos and cause departments to duplicate efforts without knowing it. 

The Rationale Behind Democratizing Data Preparation & Self-service

It’s a no-brainer that data requires cleansing and, occasionally, curation before analyzing data. 

Traditionally, this burden was laden on only the IT/data department.

Domain teams would typically submit tickets stating their requirements, and subsequently,  IT would develop the queries, reports, or dashboard as per these requirements.

However, these iterations called for a lot of back and forth due to domain teams failing to properly communicate requirements to end-users,  lack of collaboration within the teams involved, etc…

And that’s where we had a light bulb moment within the data industry…Self-Service.

Self-service is the art of augmenting end users with intuitive tools for prototype model-building and ad-hoc analysis.

More on this in the next section…

Self-service Data-Prep – Why?

Self-service Data Prep enables end-users to perform ad-hoc analysis and prototyping.

Domain teams have the ability to directly give business structure to raw data without having to rely on requirements back and forth to IT.

Although self-service data prep requires well-founded backend frameworks to allow the end-user persona to carry out preparation tasks efficiently, there’s no denying that it reduces the workload on IT.

When implementing a self-service stack, here are a few questions of high importance :

• What methods are used to acquire the needs for data sources and reports?
• What kinds of inquiries or responses are required?
• What are the users’ top strategic business concerns when obtaining the data?
• Do you balance the requirement to provide quick answers to broad inquiries and provide room for more in-depth investigation?
• What procedures (such as quality control and certification) are in place to guarantee the accuracy of data flows and published data sources?

Self-Service Data Prep – How?

Ad hoc preparation and analysis without a  standardized, regulated approach might result in duplication of effort, manual labor, and inconsistent data analysis results.

A critical factor in remediating these issues is understanding where the data comes from and, once it’s cleaned, where it will be available—essentially, the connections between the person preparing the data and the person analyzing it.

That’s why it’s crucial to develop a standardized and controlled modern stack.

Feel free to check out our webinar on The Modern Snowflake Analytics Stack With Datacoves  where we leveraged democratized data preparation in addressing a common analytics use case.

Meet Datameer: The Self-Service Data Preparation Snowflake Alternative

Datameer, as a company, has been in the business of democratizing data since the early 2000s.

Datameer is a modern analytics platform built for Snowflake and was built to foster quick and decentralized data modeling within Snowflake.

With its multi-persona approach, Datameer is the perfect Snowflake alternative for the non-technical user. 

As an all-in-one solution for visualizing and cataloging Snowflake insights, some of its salient features include the following:

– SQL Visualization

With features like our SQL preview node, users can graphically transform, preview, and keep tabs on all the transformations made in their projects without having to write any SQL code.

 – Semantic Layering

A universal semantic layer is a platform that can reduce complexity, improve security, and streamline reporting in complex environments. 

With features enabling crowd-sourced data governance, real-time integration with Snowflake, multi-persona modeling, etc. Datameer is one such platform.

– SQL Data Exploration

The Snowflake explorer is a powerful tool that enables users to explore, analyze and find patterns within their Snowflake data sets.

– Search, SQL auto-complete, and IntelliSense capabilities for quick modeling

– Ad-hoc visualization and profiling features to speed up your prototyping and increase your time-to-insight

– Code Reuse and Forward Engineering

Seamlessly schedule to publish or immediately deploy your modeled views back into Snowflake.

Additionally, every UI transformation generates corresponding SQL code for auditing and possible re-use.

Want to be a part of this?

Need to achieve standard democratized data prep within Snowflake?

Try Datameer, the Snowflake alternative for business people!