Empower your team with
data fabric and AI-assisted analytics.
data fabric and AI-assisted analytics.
Full lifecycle from discovery to production in a single cloud platform.
Catalog for workflows and data, no matter where they reside.No data lake required. Tag, document, search, and discover data based on its format, usage, structure, and location.
Automatic lineage.Enso traces your workflows providing you with automatic dependency tracking and column-level data lineage.
Data Links.Versioned proxies for files, databases, and APIs, allowing data redirection without workflow interruption. The data schema is inferred based on use within workflows, ensuring uninterrupted data flow, whether it's a CSV on SQL today or a Salesforce query tomorrow.
Unified data security and classification.Data Links sharing operates at a granular level, from complete datasets to single query results, and can be based on classification, such as importance or risk level.
Data Links can store encrypted credentials to shield against social engineering and usage of recycled or default passwords, the most common causes of data breaches.
Comprehensive access and entitlements audit.All user activity is logged, tagged, and searchable, including permitted and denied data access and modifications. In case of an incorrect update or a data leak, you can easily trace its source or revert it to previous version.
Ingest structured and unstructured data.Read and write structured data to and from any common database, including Postgresql and SQL Server, and popular formats, such as Excel, Tableau, and more.
Read and write unstructured data to and from files and APIs in various formats, including text, ASCII, JSON, XML, and more.
Clean and reshape. Ensure data quality.Address missing values, correct errors, and reshape data by transforming, combining, and filtering.
Blend and process data in‑database and in‑memory.No need to centralize data in a data lake. If data starts in a database, subsequent components run in-database, as far as possible. Otherwise, data is processed in-memory.
Enso Copilot, an explainable AI.Chat with your data. Understand precisely how AI computed the results by tracing generated flow graphs and comprehending annotations for each data transformation step.
Live, interactive data processing.Change parameters, see results live. Switch between built-in and third-party visualizations to find the best data exploration perspective. Selection is preserved, so you can understand data relations with ease.
Build and share custom components.Create and share custom components effortlessly by collapsing graphs, promoting reusable best practices across your organization.
Explore your data without accidental data overwrites.In exploratory lifecycle mode, data is written to temporary location, so you never overwrite your production data by accident. You can also define multiple lifecycle environments, such as development and production, for every Data Link.
shops_revenue_by_day day=(Equal "2023-10-29")
join node2 on=
Data.read "customers_opinions" format=JSON
`py import tensorflow as tf embedding = "https://tfhub.dev/google/nnlm-en-dim50/2" model = tf.keras.Sequential() model.add(hub.KerasLayer(embedding, dtype = tf.string)) # ... rating, confidence = ,  df = args.copy() for row in df.rows(): result = model.predict(row["opinion"]) rating.append(result.rating) confidence.append(result.confidence) df.insert(1, "rating", rating) df.insert(2, "confidence", confidence) return df`
Data.write "customers_opinions_with_ratings" format=Infer
Switch from graph to code and back.Under the hood, graphs are code. You can edit this code, and graphs will be updated. Enso is both a powerful data processing environment and an expressive, fast programming language. You can use it across the application, from creating your own data types, to scripting values of widgets.
Schedule and monitor workflows.Easily schedule recurring, time-based, or dynamic interval workflows. Trigger workflows automatically for seamless adaptability.