Compare Flatfile vs Arcade Analytics

Summary

Flatfile helps users provide their customers with a seamless data import experience hoping to eliminate rework prior to uploads and increasing the first-attempt success rates. Data can be uploaded using CSV or XLS files, or even through manual copy-pasting. The tool automatically matches 95% of imported columns using AI, machine learning and fuzzy matching and lets users analyze past data uploads. Users can view past file imports and metrics such as rows imported, recent import errors, and file upload times. The Data Mapping features allow the matching of columns and fixing of rows before the CSV data is uploaded. Users can also personalize the Flatfile importer according to their brand using custom CSS. For security, it features HIPAA compliance and 100% browser-based data processing ensuring sensitive spreadsheet data is not transmitted to their servers. Its team also provides solutions for data import issues and customizes Flatfile for their usage. ..show more

Arcade Analytics is a software allowing users to visualize data into graphs and charts. The key feature of this tool is to create easy-to-understand visualizations from complex data using queries. It runs on top of the database and users can query the database to get the data in a visual format. Arcade cloud lets users access their analytics and data from anywhere and the insights can be shared with the team and clients. The connectors visually represent relationships and connections within their datasets. There are a plethora of options that allow users to find meaningful relationships and connections. These options include changing the size, colour, background image, and layout of nodes, and filtering the visualization to only see certain sections of the data. The software integrates with many popular Relational and Graph Databases including Oracle, MySQL, PostgresSQL, Neo4j, OrientDB, TigerGraph, and JanusGraph. ..show more

Customer Data Helps in recording, accessing and managing customer information

Data Analysis Helps in analyzing stored raw data and converting them into useful reports

Data Capture Helps in gathering and extracting data from documents and transforming them into computer-readable form

Data Integration Helps in collecting and combining data from multiple data sources and offer them in a unified manner to the user

Data Migration Facilitates transferring or shifting data between computer storage types and or file formats

Data Quality Control Helps in monitoring the quality of data input and processed

Data Security Ensures secure storage of data by encryption

Information Governance Allows adopting a holistic approach to govern or manage the corporate data

Master Data Management Enables an organization to manage and integrate all of its critical corporate to a centralized point of reference

Match & Merge Helps matching data across multiple sources and to merge them for offering a better view to the data managers

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