What is Data Wrangling?

Data wrangling is the process of cleaning and unifying messy and complex data sets for easy access and analysis.

With the amount of data and data sources rapidly growing and expanding, it is getting increasingly essential for large amounts of available data to be organized for analysis. This process typically includes manually converting and mapping data from one raw form into another format to allow for more convenient consumption and organization of the data.

Data Preparation

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The Goals of Data Wrangling

Reveal a "deeper intelligence" by gathering data from multiple sources
Provide accurate, actionable data in the hands of business analysts in a timely matter
Reduce the time spent collecting and organizing unruly data before it can be utilized
Enable data scientists and analysts to focus on the analysis of data, rather than the wrangling
Drive better decision-making skills by senior leaders in an organization

Key Steps to Data Wrangling

Data Acquisition: Identify and obtain access to the data within your sources.

Joining Data: Combine the edited data for further use and analysis.

Data Cleansing: Redesign the data into a usable and functional format and correct/remove any bad data.

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Altair® Monarch®

Data You Can Trust to Make Smart Decisions

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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Altair Monarch Datasheet

Monarch is the fastest and easiest way to extract data from any source — including turning unstructured data like PDFs and text files into rows and columns.

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Spend Less Time in Spreadsheets

Spreadsheets are powerful but not designed for today’s analytics demands. See how Altair Monarch transforms data in minutes.

Use Cases

Streamline Audit Processes with Self-Service Data Preparation

Auditors are under significant pressure to keep expenditures down whether they work for an external audit firm or are part of an internal audit team. Achieving cost-effective audits requires organizations to do more with less - while maintaining or increasing audit quality. To succeed auditors not only need the right expertise and process but also the right data analytics tools.

Use Cases

Enhancing Your RPA Investment With Data Preparation

As more businesses use Robotic Process Automation (RPA) as a means to streamline operations and assess efficiency gaps, there are hurdles to fully realizing its benefits. For instance, existing data is often challenging for RPA processes to handle. Without a good solution, studies indicate that 80% of the time spent on RPA has to do with data preparation.
Discover how you can enhance your ongoing RPA investment with the right data analytics stack.

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