Monarch is a market-leading desktop-based self-service data preparation solution. Monarch connects to multiple data sources including structured and unstructured data, cloud-based data, and big data. Connecting to data, cleansing and manipulating data requires no coding.
Monarch can quickly convert disparate data formats into rows and columns for use in data analytics. Over 80 pre-built data preparation functions mean data preparation tasks can be completed quickly and error-free. More time is spent on generating value from data as opposed to making data usable to begin with.
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Why Monarch?
Reveal
Turn difficult data into smart data, leading to actionable insight to solve complex business problems. Monarch’s 30 years of experience in self-service data preparation enables more people to access, transform and utilize data to make better decisions.
Insight
Monarch enables smart decisions to be made based on accountability, insight, and trust in the data being used. Insight is found quickly, without complexity. Users of all skill levels can prepare data that will be used to inform their opinions.
Believe
Self-service data preparation that is agile, controlled, trusted, and accurate means errors are avoided, and valuable resources are not wasted using tools that are difficult to use. Decisions can be made immediately, and with confidence.
Key Features
Ease of Use
Turn difficult data into smart data, leading to actionable insight to solve complex business problems. Monarch’s 30 years of experience in self-service data preparation enables more people to access, transform and utilize data to make better decisions.
Self-Service Data
As an industry leader for 30 years, Monarch is the fastest and easiest way to extract data from dark, semi-structured data like PDFs and text files, as well as big data and other structured sources. Build trust in your metrics with auditable change histories and clear data lineage tracking. No coding is required.
Reduce Costs
Desktop-based self-service data preparation eliminates the need for IT to extract data, which is often very time-consuming and labor intensive. Automated repeatable processes with reusable models and workspaces allows workers to spend their time analyzing data instead of preparing it for analytic needs.