Sisense, providing an AI-driven platform for infusing analytics everywhere, is offering Sisense Notebooks, a new code-first functionality within Sisense Fusion Analytics that empowers data analysts with the tools they need to conduct advanced analysis using Structured Query Language (SQL) and Python.
As part of the Sisense Fusion Platform 2012.12 release, Notebooks will enable data analysts to query data from any data source, visualise results in custom charts, and take their analytics efforts further using procedural code before visualisation.
Notebooks will help boost data analyst productivity with integrated workflows, source control, advanced security, and much more, allowing them to conduct ad hoc analysis on disparate datasets — in a highly customisable fashion in SQL or Python — within a single platform for both in-depth analysis and BI that preserves data security and integrity, according to the vendor.
“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 organisation,” said Ashley Kramer, chief product and marketing officer at Sisense. “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.”
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Additional key features of Sisense Notebooks designed to accelerate the capabilities of analysts to solve important business decision-problems include:
- Integrated workflows. Go from model design to advanced analysis to visualization to source control, all in one location, and with the highest degree of data security.
- Analysis using SQL or Python. Capabilities include SQL to charts, SQL to Python to charts, and SQL to R to charts, coming soon. Along with these features comes the best in class SQL and Code editor giving analysts the ability to quickly perform their research in a continuous and efficient manner.
- Orchestrate information with custom queries. Advanced operations such as window functions and common table expressions allow analysts to glean more complex insights from datasets with high accuracy and precision, eliminating typical self-service pain points, such as semantic models that limit the type of questions business users can ask.
- Notebooks allows for best-in-industry collaboration during a developers exploratory analysis before providing an answer or visualisation to a problem, and then eventually be able to share within the same product offering, coming soon.
Sisense Fusion Analytics offers self-service capabilities as well as tools for data analysts, so any type of intelligence may be gleaned from business data. Notebooks will fill a gap compared to self-service solutions by allowing for integrated custom analysis.
Sisense is also introducing the beta version of an integration with Git to enable software developers and product teams to manage the lifecycle of their dashboards and codes, designed to further operationalize and scale analytics across the enterprise. The feature will be fully integrated in 2022.
