Best Data Preparation Software for Cloud

SparkGrid is a user-friendly data management tool that simplifies communication with Snowflake by offering a tabularized interface similar to standard spreadsheet applications. It allows users to perform complex data tasks without needing extensive technical knowledge, making Snowflake more accessible. SparkGrid supports multi-field editing, SQL statement previews, and built-in error handling and security features to ensure data integrity. The intuitive graphical user interface enables easy navigation, selection, and manipulation of data such as adding or removing rows and columns. By bridging the gap between visual data management and SQL queries, SparkGrid empowers teams to work efficiently. It is designed to enhance productivity and democratize access to Snowflake’s powerful data capabilities. Available on AWS's marketplace, just search "Sparkgrid AWS Marketplace" Or contact us for custom implementation options.

An industry leader with over 30 years of experience in data discovery and transformation, Altair Monarch offers the fastest and easiest way to extract data from any source. Simple to construct workflows that require no coding enable users to collaborate as they transform difficult data such as PDFs spreadsheets, text files, as well as from big data and other structured sources, into rows and columns. Whether data is on premises or in the cloud, Altair can automate preparation tasks for expedited results and deliver data you trust for smart business decision making. To learn more about Altair Monarch or download a free version of its enterprise software, please click the links below.

Dataiku is an advanced data science and machine learning platform designed to enable teams to build, deploy, and manage AI and analytics projects at scale. It empowers users, from data scientists to business analysts, to collaboratively create data pipelines, develop machine learning models, and prepare data using both visual and coding interfaces. Dataiku supports the entire AI lifecycle, offering tools for data preparation, model training, deployment, and monitoring. The platform also includes integrations for advanced capabilities like generative AI, helping organizations innovate and deploy AI solutions across industries.

Oracle Analytics is a complete platform for every analytics user role. AI and ML are embedded throughout the platform to accelerate productivity and power better business decisions. Choose either Oracle Analytics Cloud, our cloud native service, or our on-premises solution, Oracle Analytics Server, both of which help you avoid compromising security and governance. Oracle Analytic addresses all needs of business users from data to decision. Oracle Analytics can help you solve your business problems with built in data preparation and enrichment, no-code machine learning and industry leading data visualization.

Oracle Big Data Preparation Cloud Service is a managed Platform as a Service (PaaS) cloud-based offering that enables you to rapidly ingest, repair, enrich, and publish large data sets with end-to-end visibility in an interactive environment. You can integrate your data with other Oracle Cloud Services, such as Oracle Business Intelligence Cloud Service, for down-stream analysis. Profile metrics and visualizations are important features of Oracle Big Data Preparation Cloud Service. When a data set is ingested, you have visual access to the profile results and summary of each column that was profiled, and the results of duplicate entity analysis completed on your entire data set. Visualize governance tasks on the service Home page with easily understood runtime metrics, data health reports, and alerts. Keep track of your transforms and ensure that files are processed correctly. See the entire data pipeline, from ingestion to enrichment and publishing.

For data teams looking to increase the availability of trusted data, Astronomer provides Astro, a modern data orchestration platform, powered by Apache Airflow, that enables the entire data team to build, run, and observe data pipelines-as-code. Astronomer is the commercial developer of Airflow, the de facto standard for expressing data flows as code, used by hundreds of thousands of teams across the world.

With TIMi, companies can capitalize on their corporate data to develop new ideas and make critical business decisions faster and easier than ever before. The heart of TIMi’s Integrated Platform. TIMi’s ultimate real-time AUTO-ML engine. 3D VR segmentation and visualization. Unlimited self service business Intelligence. TIMi is several orders of magnitude faster than any other solution to do the 2 most important analytical tasks: the handling of datasets (data cleaning, feature engineering, creation of KPIs) and predictive modeling. TIMi is an “ethical solution”: no “lock-in” situation, just excellence. We guarantee you a work in all serenity and without unexpected extra costs. Thanks to an original & unique software infrastructure, TIMi is optimized to offer you the greatest flexibility for the exploration phase and the highest reliability during the production phase. TIMi is the ultimate “playground” that allows your analysts to test the craziest ideas!

DataPreparator is a free software tool designed to assist with common tasks of data preparation (or data preprocessing) in data analysis and data mining. DataPreparator can assist you with exploring and preparing data in various ways prior to data analysis or data mining. It includes operators for cleaning, discretization, numeration, scaling, attribute selection, missing values, outliers, statistics, visualization, balancing, sampling, row selection, and several other tasks. Data access from text files, relational databases, and Excel workbooks. Handling of large volumes of data (since data sets are not stored in the computer memory, with the exception of Excel workbooks and result sets of some databases where database drivers do not support data streaming). Stand alone tool, independent of any other tools. User friendly graphical user interface. Operator chaining to create sequences of preprocessing transformations (operator tree). Creating of model tree for test/execution data.