Sisense has launched SiSense Notebooks, a solution with a code-first approach designed to appeal to data analysts. The solution enables data analysts to build advanced analysis using Structured Query Language (SQL), Python and R. It is a refreshing change from the usual announcements of low code/no code deployments for business users. SiSense is appealing directly to data analysts. These are the data science innovators who can make a real difference within their organisations.
As a customer, John Will, Director, Global Ops at Arista Networks, noted, “The Sisense Notebooks product offering is a fresh, innovative idea that I haven’t seen in other visualization BI tools. It appears to be a very interesting enhancement to the existing Sisense portfolio of capabilities that we look forward to experimenting with, and learning more about.”
The first version of Notebooks was included in the 2021.12 release of SiSense. Pat Bhatt, Director of Product Management, Cloud Analytics, at Sisense, explained what it delivers in a blog, saying: “With Notebooks, users can query data from any data source, visualize results in custom charts, or even take analytics further using procedural code before visualization. In addition to visualization, outputs can be materialized or serialized to any destination, including cloud data warehouses.
“Notebooks helps boost data analyst productivity with integrated workflows, source control, advanced security, and much more.”
What is in Notebooks
Notebooks provide a single self-service environment. It can be used by data analysts to create integrated workflows using SQL, Python and R. There is no longer a need to move to another environment to design models, create advanced analysis and visualisations.
There is a beta version of an integration to GitHub in this first release. It will enable developers and product teams to manage the lifecycle of their dashboards and codes. This integration will become generally available and fully integrated in 2022.
Notebooks includes window functions and common table expressions enabling data analysts to create complex insights from datasets. It gives them greater freedom than is often available within no-code/low code solutions. Using the SQL and code editor, analysts can code SQL to charts and SQL to Python to charts. The ability to code SQL to R to charts is coming soon.
Security and collaboration
The same high level of security underpins notebooks as the rest of the SiSense platform. This is just a component of the Sisense differentiation. As Bhatt noted, “Notebooks offers an integrated workflow so that the analyst goes from model design to advanced analysis to visualization to source control, all in one location, and with the highest degree of data security.”
In future releases, Sisense will also enhance the collaboration features of Notebooks. It will enable data analysts to share code and work collaboratively.
Ashley Kramer, Chief Product and Marketing Officer at Sisense, commented: “The market is full of tools that offer fragmented workflows and manual procedures, which compromise productivity, accuracy, and security and slow down the time-to-insight for anyone looking to make a data-driven decision at the organization.
“With Notebooks, we’re taking a code-first approach to help infuse insights and scale the decision making across the enterprise, creating a powerful partnership between business users and analysts.”
Enterprise Times: What does this mean
Sisense is also focusing on those individuals in organisations that want to do their own modelling. Its tools will allow them to create their own data models and derive differentiating insights for their business through Notebooks.
Aaron Peabody, CTO at Untitled Firm, commented: “The offering gives Data Analysts the tools they need to conduct advanced analysis, which ultimately increases efficiency and productivity. In a lot of advanced cases, SQL by itself just won’t cut it for sophisticated modeling workflows or intricate Ad-Hoc queries.
“Users need a more robust solution set of tools such as Python as well as the underlying packages these languages offer. Utilizing these languages in harmony with SQL unlocks a more dynamic modeling experience for Sisense Fusion Analytics users. The Notebooks offering has proven to speed time to insight by lowering modeling barriers through a unified environment that enables the Data Analyst.”
SiSense has also published a whitepaper to highlight three use cases for Notebooks. It also analyses why this new product is important and why it will make a difference. It will be interesting to see how SiSense develops Notebooks for data scientists and its platform for business users. The trick will be taking the learnings from the former to build into the latter.
