Empower everyone to explore data

A self service business intelligence and analytics solution built for your cloud data warehouse. Empower everyone to explore data.

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Overview

Sigma is a self service BI and data analytics tool for cloud data warehouses. Build dashboards, charts, tables, and reports in a familiar spreadsheet interface — all without any programming involved.

With the advancement of technology and the internet, more and more companies are accumulating data everyday. There isn't a tool out there that allows business users to gain deeper insights into their data without relying on the data team, which in itself could take weeks to months. Sigma is the only tool that is made specifically for business user to be able to access, clean, analyze, and visualize their own data. 

Time: 2016 - present     Role: Product designer, researcher      Link: website

Understanding the Problems

Until relatively recently data was structured and small in size. It was able to be analyzed either manually or with the use of simple tools and algorithms. With the advancement of technology and the internet, large amounts of data is accumulating everyday. Every click, purchase, and customer interaction generates data. This is often semi-structured, or completely unstructured.

 

To help us make sense of this growing mass of unstructured data we need more complicated analytical tools and sophisticated algorithms.

The Problems

Specific to certain users

Today data scientists are the professionals who knows how to tease actionable insights out of gigabytes of data. Without these experts who turn cutting-edge technology into actionable insights, Big Data is nothing. They spend a lot of time in the process of collecting, cleaning, and munging data, because data is never clean. This process requires persistence, statistics, and software engineering skills.

Requires SQL

Structured Query Language (SQL) is the standard programming language used to communicate with a database. It is primarily used to find and pull information from large databases (relational database management systems).

SQL has become a very important tool in a data scientist’s toolbox since it is critical in accessing, updating, inserting, manipulating and modifying data. It helps in communicating with relational databases to be able to understand the dataset and use it appropriately.

Bottleneck = Frustration

With data informing just about every business decision, business users currently require the help of data teams/data scientists to get answers to their data questions. This could take anywhere from 1 week to 3 months. 

 

Frustration goes hand-in-hand with data teams as they are professionals who are qualified to create complex models and write scripts are instead being tasked with manually pulling basic reports for their managers.

Nothing Works

Needs SQL Knowledge or proprietary language

Steep learning curve

Not for the business user

Not flexible

Only does certain things well

Requires multiple products

Very expensive

Self Service

The Goals

This necessitates a self-service model that empowers the domain experts, aka business users, to be able to explore and answer their own data questions. 

 

Sigma is a BI/data analytics product for the cloud data warehouse – Snowflake, Google big query, Microsoft Azure.

The future is the cloud so we targeted only c

No SQL

Familiar Spreadsheet UI

Let the domain experts answer their toughest questions and drive insights.

There is one product that everyone is familiar with.

Empower the domain expert

Let the domain experts answer their toughest questions and drive insights.

Process

Series A, 8th Employee

When I joined, the company was at Series A and I was the 8th employee. Six months after I joined, everything got scratched and we had to start from ground zero. I became the only product designer who worked with the two co-founders to begin a journey of finding what

Research, research, research

Starting from scratch was a bit nerve wracking but at the same time exhilarating because of the potential to build a product and company from the ground up. Because we didn’t have any researchers or PM, I interviewed users in our own network at small, medium, and large sized companies to see how they are getting access and working with data. 

After meeting with a number of folks from small all the way to medium and large companies. we discovered

1) Users are used to a tabular UI

2) 2 sides: person making data available to others vs the person consuming the data

3) Business users (non technical) wouldn’t want to view dashboards in Excel/G-sheets, they wanted something simple that’s on the web

4) They also didn’t want to download anything to add to desktop. Wanted it on the web

5) The #1 most commonly used tool amongst all business users was Excel (spreadsheet)