Building The Next Generation B.I. Platform. Infuse Analytics Everywhere!

The Challenge
Redesign and integrate Periscope Data’s B.I platform into the Sisense product. Design a new tool that allows data analysts to create complex multi cell analysis using markup, text, and code (SQL, Python and R) in a single document.

My Role
Lead Product Designer

B2B to B2C

What’s Sisense & What Do They Do?

Sisense is a business intelligence (BI) solution that provides advanced tools to manage and support business data with analytics, visuals and reporting. The solution allows businesses to analyze big datasets and generate relevant business trends for them. Sisense allows businesses to combine data from many sources and join them into a single database. Users can then perform slicing and dicing over the complete data set using multiple filters and built-in analytic tools. Sisense can be deployed on-premises or hosted in the cloud as a SaaS application. Sisense’s customers include General ElectricNasdaqPhilipsSpotify, & Wix.


“Sisense allows data to be accessible in a way that everyone can see it, understand it, and filter it independently. That was probably the biggest win for us.”

The Market Size

By 2020, 90% of business professionals and enterprise analytics say data and analytics are key to their organizations digital transformation initiatives. According to a recent research study, approximately, 58% of organizations worldwide plan to adopt big data technology in 2018. The organizations will adopt hybrid IT infrastructure management capabilities. The growing adoption of big data and AI in industries including IT & Telecom, BFSI, and Healthcare among others is further fueling the demand of the big data analytics market.


Sisense's Customers Are Sized Between 50M to 1B USD


Businesses Leverage The Power of Sisense


Active Users

Sisense Acquires Periscope Data.

Periscope Data Is Now Sisense For Cloud Data Teams

Periscope Data joined forces with Sisense in a merger that makes it possible to deliver an end-to-end BI and analytics. The merger now gives data science teams access to a cloud platform with capabilities like cloud-native data integration, advanced analysis with SQL, R, and Python, and integration with production cloud machine learning systems.

Periscope Data is recognized as a “game-changer” by Next Wave Business Intelligence and the 4th fastest-growing company in North America by Deloitte. The merger gives Sisense over $100M in annual revenue with a global team of 700 data and analytics experts.

Read more at Techcrunch

My Role As The Design Lead

As a lead designer I help shape the product strategy and vision. I work in a cross functional team of product managers, engineers, general managers and senior leadership to drive product decisions grounded in both qualitative and quantitative research. In my role, I define the user experience, interactions, and user interface through user flows, information architecture, wireframes, visual designs and build functional prototypes to validate designs. As a lead, I own and define the user testing and user research process and define the design process for non-product design members.

Understanding The Problem Space

The acquisition of Periscope Data brought a few challenges. Both Sisense and Periscope Data are 2 different types of B.I. platforms that function differently and serve different markets. Sisense is an on-premise solution targeted to non-technical users who rely on a drag-and-drop user experience to create data models, dashboards and live reports. Periscope Data on the other hand, is a SaaS cloud based B.I. solution that targets advanced technical analysts who use code (SQL, Python & R) to create dashboards and live reports. Because Periscope Data focuses on the technical data analysts but also their workflow; we discovered that over 60% of all Periscope Data customers performs what is known as ad hoc reporting & analysis. This process involves answering a single business question, from data to be used 1 time, to make a business decision. Since Periscope Data is now Sisense, we need to merge both products and unify both product experiences, while addressing the growing need of ad hoc reporting & analysis that Periscope Data did not support in the past.

Periscope Data

The old Periscope Data’s platform focused on powering a single chart from 1 code based, rather than the growing need of ad hoc reporting & analysis.

Sisense For Cloud Data Teams (CDT)

The new platform allows analysts to explore and iterate upon complex data sets to arrive at the right business answer.

The Solution

Periscope Data Is Now Sisense For Cloud Data Teams

Sisense for Cloud Data Teams allows businesses to connect to any cloud data source to explore their data and build powerful analysis quickly.

  • Iterate On Ideas
  • Add Multiple Content Blocks
  • Use Multiple Code Languages (SQL, Python & R)
  • Perform Data Analysis Faster
  • Build Rich & Compelling Data Stories With Visualizations, Text & Hyperlinks
Never Be Confined To 1 Place

Add Multiple Content Blocks

Sisense For Cloud Data Teams brings a new kind of interactiveness and flexibility for a better code editing experience & data analysis process. Data analysts can now tackle large complex data by writing live code in individual blocks that can be ran independently, making it easier to experiment, explore and develop faster analysis.

Answering Data Questions Is Complex

Iterate On Ideas To Arrive At Your Answer

Sisense For Cloud Data Teams allows analysts to experiment with their codebase to arrive at answers quickly. Analysts no longer have to write large datasets in one confined area. Instead, analysts can break their codebase into smaller areas and run each section of the code individually, change things and see the results of that change instantly. This process of experimentation allows analysts to build upon many ideas and arrive at a final hypothesis through a process of experimentation and iteration.

Throw Those Dull Analysis Out The Window

Tell Compelling Data Stories With Text, Images, Hyperlinks & Visualization

Sisense For Cloud Data Teams integrates code and its output into a single document that combines visualizations, narrative text, mathematical equations, images and hyperlinks to make analysis more transparent, understandable, repeatable, and shareable.

My Research Approach…How I Arrived To a Solution

Business Goals

The biggest differentiator about the Sisense for Cloud Data Teams product is the ability for businesses to be able to turnaround core reporting and answer complex questions in their first hours of using the product. The ability to write SQL, Python and R against modeled and unmodeled data allows Data Analysts and Data Scientists to rapidly explore, transform and visualize data with the flexibility of code, and leverage advanced statistical techniques to create analyses of a higher caliber and extend from descriptive to predictive insights.


Merge both companies (Sisense & Periscope Data) into 1.

Offer a verity of different packages to meet the demands of our customers.

Unify the product experience.

Strengthen Sisense as a SaaS cloud company.

Market Dynamics

Increased adoption of cloud data warehouses.

Companies are collecting data from more sources and leveraging scales solutions to store and process. This leads to increased hiring of data analysts and data scientists to make sense of their data and stay competitive in the market.

Increased investment in data science.

Understanding Our Customers

Sisense for Cloud Data Teams (previously Periscope Data) serves 3 major customers: the data engineer, data analyst and the business user. Each play an important role within a company. A data engineer builds data pipelines that transform raw, unstructured data into formats data scientists can use for analysis. They are responsible for creating and maintaining the analytics infrastructure that enables almost every other data function.  data analyst is someone who examines information using analysis tools and uses raw data to help their employers or clients make important decisions by identifying various facts and trends. They transform business questions into reports through the use of code to drive visualizations that uncovers ‘why’ something is happening. A business user is responsible for bridging the gap between IT and the business, determining requirements and deliver data-driven recommendations and reports to executives and stakeholders. A typical question could be ‘why do we see a sudden drop in our usage’. A business user will work with the data analyst to understand and uncover the needs of the business through data.

Who’s Our Customers?

Data engineer, data analyst & the business user

Our Target Persona

The Data analyst

Why We Value this ‘Persona’?

  • Data analysts hold the buying power over the tools they use
  • Data analysts create all the reporting within a company
  • Data analysts transform large complex business questions into a tangible result 

The Data Analyst’s Journey

Finding Out Analysts conduct something Called ‘Ad Hoc Analysis’

After interviewing several data analysts and discovering the many different tasks involved in the analysis process to create dashboards & live reports; I found that reporting is about 60% of their overall duty. A major task that takes 40% of an analysts time is answering 1 off questions related to a report delivered to a business user. This particular task is called ‘Ad hoc analysis’ which is any kind of analysis digging deeper into 1 specific area of a live report or dashboard, to obtain more details about it for a single use. Many times, ad hoc analysis is done in response to an event, such as a sudden dip in production or loss of customers where a business user needs to understand why this sudden dip in production is happening. An analysts may create a report that does not already exist or drill deeper into a static report to get details about accounts, transactions or records on the spot. Prior to Sisense acquiring Periscope Data, this user need or problem was not solved until now.

The End-to-End Process Of A Data Analyst

Painpoints Discovered Along The Journey

Data Exploration

Finding the right data

Fishing through many databases

Cleaning the data

Translating a business question into quantitative results

Code Editing

Building a hypothesis with code

Small area to write code

Losing track of what was tried

Opening many windows or tabs

The trial & error process

Problem Statement

Analysts are forced to develop complex analysis in confined areas, making the iteration process of writing and testing code to drive business decisions slow and frustrating.

Areas Of Opportunity

After reviewing the analyst's journey, I identified a few areas in which we can enhance their workflow and create a better experience. These areas of opportunities were then validated with end-users to further enhance their process.

Opportunity #1

Enhance the iteration process & help develop faster analysis.

Opportunity #2

Make complex code easier to understand.

Opportunity #3

Break analysis into smaller parts & reference different areas of code.

Opportunity #4

Tell rich data stories with charts, images, videos & text.

How Might We

Empower analysts to develop and iterate upon many ideas using code in 1 environment to answer complex questions and tell compelling data stories through visualizations to drive business decisions.

Design Phase


In order to develop this new product that touches upon user & business needs, the design process uses heavy amounts of design iterations, user feedback and testing to validate our direction.

Design Strategy & Research Plan

To kick start things, I developed a 12 week plan to start design and research. The 12 weeks will uncover user needs, desirability & market fit through user research and design iterations. User testing sessions involve a series of moderated testing, 1-on-1 user interviews and surveys to assess the customer’s needs, understand their pain points and areas of frictions. The focus for Design is to discover areas of improvements in the overall experience and to develop alternative design iterations, generate new ideas, and to validate assumptions with high & low fidelity UI designs.

Methods Used

Research Methods

Moderated remote testing


1-on-1 user interviews


A/B testing

Design Methods

Concept sketching


Low-fidelity design mocks

High-fidelity design mocks

Designing Around Our Areas Of Opportunities & H.M.W

Going forward I used our ‘areas of opportunities’ and the ‘how might we statement’ as a bases for developing designs. The wireframes below is the first phase in my design process and used to understand user needs.

Areas Of Opportunities

Opportunity #1

Enhance the iteration process & help develop faster analysis.

Opportunity #2

Make complex code based easier to understand.

Opportunity #3

Break analysis into smaller bits & reference different areas of code.

Opportunity #4

Tell rich data stories with charts, images, videos & text.

H.M.W Statement

Empower analysts to develop and iterate upon many ideas using code in 1 environment to answer complex questions and tell compelling data stories through visualizations to drive business decisions.

Wireframes: Round #1

The first set of wireframes are based on opportunity #1 (Enhance the iteration process & help develop faster analysis) using the Periscope look & feel. At this point in time, both Sisense and Periscope Data did not have a clear direction for how the product should be merged. Because of this ambiguity, I used the Periscope look & feel to jumpstart design and the testing phase. The wireframes illustrate the concept of adding multiple charting blocks allowing data analysts to see multiple views of their data. As a product group, we assumed this ability would aid analysts in developing faster analysis but our assumption proved to be wrong.

Customer Feedback

After a few rounds of customer feedback, the wireframes prove to be a step forward in the right direction, analysts gave positive feedback and wanted to have multiple kinds of visualizations to help expand their view of the data, but our customers wanted more. In order to answer a business questions through data, our customers need the ability to make many iterations of a data set, to write and run code and have the ability to rewrite and test their dataset in 1 environment. The iteration of a codebase or dataset is the highest and most  valuable area to pursue going forward.

Wireframes Round #2

Taking the feedback from the last set of wireframes, the main focus here is the ability to add many blocks to enhance the code iteration process. These blocks give analysts a way to brake their code into smaller parts and to test their results in 1 area. The wireframes illustrate the ability to 1) create code blocks, 2) write code within a block and 3) run the code block to see the results. Each code block can be ran independently from one another, giving the analyst the power to see and understand how their dataset progressed into a finalized outcome. In addition, blocks can be used for text, images and different forms of visualizations to create a narrative around a dataset. Our customers responded very positively to this new direction of adding content blocks, and proved to be an important key in laying out the foundation of this new product. This new ability of adding code blocks to test and iterate upon a dataset solves our user’s frustration of writing and testing large datasets found in traditional code editors and makes the iteration process easier and intuitive. By the end of this testing phase it was determined that this product should fit within the Sisense look and feel in order to promote the merger of Periscope Data into Sisense.

Starting Designs Based On Our System

After wrapping up testing wireframes with users, it was determined that Sisense’s look & feel will drive all new products to help promote a unified company. The next phase for design is to incorporate the Sisense look & feel while incorporating user feedback to further enhance the iteration process. Since Sisense focuses on nontechnical users to create live reports and dashboards, the look-&-feel  promotes the idea of ‘friendliness’ and ‘simplicity’, it’s important to carry these same ideas into our new platform that focuses on technical users.

Design Iteration #1

The Biggest Value Is Adding Content

Throughout this journey of understanding the needs of data analysts, the biggest value is the ability of adding multiple blocks to write and test analysis with code. In these designs, I tried a few different ways of adding blocks to discover a solution that promotes the code iteration process. From the wireframes, analysts expressed an interest in knowing where new blocks are added. This design uses a placeholder as an indicator of where new content will be added to the page.  By clicking the ‘+ Code’ or ‘+ Markdown’ a new block appears in the placeholder area, giving a visual indication of where new content is added.

Customer Feedback Designs

Data analyst, like many developers love maximizing space to code, and this design created less space to work with. Analyst did however preferred the bottom placement of the buttons; the placement gave analysts a visual cue that blocks could be added underneath other blocks. I used this bottom placement as a backbone for future design iterations while also maximizing the space in the editor for analysis.

Design Iteration #2

Placing The Buttons On The Bottom Worked….Let’s Optimize It!

In this design, I focused on maximizing space for the purpose of writing more code while reducing the size of the buttons. Analyst expressed the importance of having ample space to code, the previous design took too much vertical space leaving little screen real estate for code. To solve the issue of space, I designed a series of floating buttons to add additional content, and reduced its size to give analysts more space for analysis. Analysts want and need the ability to add lots of content while having plenty of room dedicated for code.

Customer Feedback Designs

After reviewing the designs with our customers, the smaller sized buttons help to maximize space of the editor but 2 out of 5 analysts struggled to locate them. During my interview sessions, I uncovered that the empty space around the buttons caused users to overlook them. In my next iteration, I focused my design efforts on better placement of the buttons and improved visibility.

Design Iteration #3

Finding The Best Solution

In this design iteration, I placed the add more content buttons on the actual content blocks. After user-testing this method 5 out of 5 analysts were able to see the buttons and understood that new content is added to the bottom of an already existing block. Because of the linear progression of writing code from top down, the bottom placement on the content area allows analysts to see and create another block with ease. This new design is able to maximize the area for code while allowing analysts to see and create many blocks for an iterative approach to answering complex business questions. Analysts using this method can now brake large datasets into smaller pieces, run individual parts of a dataset to see if their hypothesis is correct, write new code and retest until they arrive to a final result. By giving the user the power to add multiple blocks became the key factor in solving our user’s need to have a tool that supports an iterative process of writing, running and retesting datasets.

Current State

Sisense For Cloud Data Teams Is Still Under Development

🚀 Launching Soon 🚀

We currently have over 50 Beta customers using our editor to perform data analysis. Across the board, our customers are able to complete complex analysis faster than other tools in the market today. Sisense for cloud data teams is still under development, we’re constantly rolling in new customers everyday and learning more and more. 

Our Customers Love Our New Workflow!

“That would be absolutely insane, I would love that!”

Maia PaddockData Scientist at Seasoned

“I absolutely would use it today.”

Kristin EmardManager; Analytics & Insights at Boehringer Ingelheim


Josh ZalingerData Scientist from EZ Cater
Want To Learn More?

Contact me!

For details on my process & to learn more about this case study, feel free to reach out.