Best Data Management Software for Jupyter Notebook - Page 2

With a huge collection of analytical features, AnzoGraph DB can enhance your analytical framework. Watch this video to learn how AnzoGraph DB is a Massively Parallel Processing (MPP) native graph database that is built for data harmonization and analytics. Horizontally scalable graph database built for online analytics and data harmonization. Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supports Labeled Property Graphs (LPGs). Access to many analytical, machine learning and data science capabilities help you achieve new insights, delivered at unparalleled speed and scale. Use context and relationships between data as first-class citizens in your analysis. Ultra-fast data loading and analytical queries.

Open source data governance suite for databases and data lakes. Tokern is a simple to use toolkit to collect, organize and analyze data lake's metadata. Run as a command-line app for quick tasks. Run as a service for continuous collection of metadata. Analyze lineage, access control and PII datasets using reporting dashboards or programmatically in Jupyter notebooks. Tokern is an open source data governance suite for databases and data lakes. Improve ROI of your data, comply with regulations like HIPAA, CCPA and GDPR and protect critical data from insider threats with confidence. Centralized metadata management of users, datasets and jobs. Powers other data governance features. Track Column Level Data Lineage for Snowflake, AWS Redshift and BigQuery. Build lineage from query history or ETL scripts. Explore lineage using interactive graphs or programmatically using APIs or SDKs.

Okera, the Universal Data Authorization company, helps modern, data-driven enterprises accelerate innovation, minimize data security risks, and demonstrate regulatory compliance. The Okera Dynamic Access Platform automatically enforces universal fine-grained access control policies. This allows employees, customers, and partners to use data responsibly, while protecting them from inappropriately accessing data that is confidential, personally identifiable, or regulated. Okera’s robust audit capabilities and data usage intelligence deliver the real-time and historical information that data security, compliance, and data delivery teams need to respond quickly to incidents, optimize processes, and analyze the performance of enterprise data initiatives. Okera began development in 2016 and now dynamically authorizes access to hundreds of petabytes of sensitive data for the world’s most demanding F100 companies and regulatory agencies. The company is headquartered in San Francisco.

lakeFS enables you to manage your data lake the way you manage your code. Run parallel pipelines for experimentation and CI/CD for your data. Simplifying the lives of engineers, data scientists and analysts who are transforming the world with data. lakeFS is an open source platform that delivers resilience and manageability to object-storage based data lakes. With lakeFS you can build repeatable, atomic and versioned data lake operations, from complex ETL jobs to data science and analytics. lakeFS supports AWS S3, Azure Blob Storage and Google Cloud Storage (GCS) as its underlying storage service. It is API compatible with S3 and works seamlessly with all modern data frameworks such as Spark, Hive, AWS Athena, Presto, etc. lakeFS provides a Git-like branching and committing model that scales to exabytes of data by utilizing S3, GCS, or Azure Blob for storage.

Understanding health issues often requires combining complex and heterogeneous data sources, even in the context of single-country interventions. Data can come from HMIS platforms such as DHIS2, from individual tracking systems, from custom software built to address specific issues, or from various Excel reports provided by health experts. Having such diverse data in disconnected silos is often the biggest obstacle to an efficient exploration and analysis process. It also makes collaboration difficult, and many data analysts working on health data end up developing ad-hoc scripts and visualisations on their own laptops and communicating their results in scattered publications from which it is hard to get unified insights. To address this issue, Bluesquare has built OpenHexa, a cloud-based data integration platform consisting of three components, extraction, analysis & visualization. This platform is mostly based on mature open-source technologies.

Enabling all enterprise’s AI/ML initiatives to result in consistent and positive impact. Data scientists deserve a solution that makes all their experiments reproducible, every asset discoverable and simplifies knowledge transfer. Managers deserve a dedicated data science solution. to secure knowledge, automate reporting and simplify reviews and processes. Vectice is on a mission to revolutionize the way data science teams work and collaborate. The goal is to ensure consistent and positive AI/ML impact for all organizations. Vectice is bringing the first automated knowledge solution that is both data science aware, actionable and compatible with the tools data scientists use. Vectice auto-captures all the assets that AI/ML teams create such as datasets, code, notebooks, models or runs. Then it auto-generates documentation from business requirements to production deployments.

Great Expectations is a shared, open standard for data quality. It helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. We recommend deploying within a virtual environment. If you’re not familiar with pip, virtual environments, notebooks, or git, you may want to check out the Supporting. There are many amazing companies using great expectations these days. Check out some of our case studies with companies that we've worked closely with to understand how they are using great expectations in their data stack. Great expectations cloud is a fully managed SaaS offering. We're taking on new private alpha members for great expectations cloud, a fully managed SaaS offering. Alpha members get first access to new features and input to the roadmap.

Everything you need to make better business decisions. The Fosfor Decision Cloud unifies the modern data ecosystem to deliver the long-sought promise of AI: enhanced business outcomes. The Fosfor Decision Cloud unifies the components of your data stack into a modern decision stack, built to amplify business outcomes. Fosfor works seamlessly with its partners to create the modern decision stack, which delivers unprecedented value from your data investments.

Connect to data wherever it lives, even across a disparate universe. Data and model enrichment is the #1 way to increase and enhance acquisition and retention. Through machine learning, you will unlock new insights by bringing proprietary models, like propensity models, and data together in a protected way to supercharge your customer profiles and models and scale rapidly. It’s not enough to enrich the data. Your team must seamlessly go from insight to activation. Automate audience segmentation and immediately push your campaigns across disparate channels. Be smarter about who you target to save on budget and churn. Know where to target and when. Have the tools to act on data at the moment. Identifying the entire customer journey, including different types of data, has always been a challenge. As privacy regulations get stricter and data becomes more distributed, secure and easy access to those intent signals is more critical than ever.

Sync, search and manage all the work across your data science team. Zepl’s powerful search lets you discover and reuse models and code. Use Zepl’s enterprise collaboration platform to query data from Snowflake, Athena or Redshift and build your models in Python. Use pivoting and dynamic forms for enhanced interactions with your data using heatmap, radar, and Sankey charts. Zepl creates a new container every time you run your notebook, providing you with the same image each time you run your models. Invite team members to join a shared space and work together in real time or simply leave their comments on a notebook. Use fine-grained access controls to share your work. Allow others have read, edit, and run access as well as enable collaboration and distribution. All notebooks are auto-saved and versioned. You can name, manage and roll back all versions through an easy-to-use interface, and export seamlessly into Github.

Data is used in every aspect of a processing plant or facility, it is underlying most operational processes, most business decisions, and most environmental events. Failures are often attributed to this same data, in terms of operator error, bad sensors, safety or environmental events, or poor analytics. This is where APERIO can alleviate these problems. Data integrity is a key element of Industry 4.0; the foundation upon which more advanced applications, such as predictive models, process optimization, and custom AI tools are developed. APERIO DataWise is the industry-leading provider of reliable, trusted data. Automate the quality of your PI data or digital twins continuously and at scale. Ensure validated data across the enterprise to improve asset reliability. Empower the operator to make better decisions. Detect threats made to operational data to ensure operational resilience. Accurately monitor & report sustainability metrics.

A Chrome extension that operates your analytics apps for you. MinusX is the fastest way to get insights from data. Interop with MinusX to modify or extend existing notebooks. Select an area and ask questions, or ask for modifications. MinusX works in your existing analytics tools like Jupyter Notebooks, Metabase, Tableau, etc. You can use minusx to create analyses and share results with your team, instantly. We have nuanced privacy controls on MinusX. Any data you share, will be used to train better, more accurate models). We never share your data with third parties. MinusX seamlessly integrates with existing tools. This means that you never have to get out of your workflow to answer questions. Since actions are first-class entities, MinusX can choose the right action for the right context. Currently, we support Claude Sonnet 3.5, GPT-4o and GPT-4o mini. We are also working on a way to let you bring your own models.

We help businesses unlock the power of 1st party data collaboration without the risks. Transform your consumer data from a liability to a revenue-generating asset. Thrive in the post-cookie world with 1st party consumer data. Collaborate with more partners to unlock more value for your customers. Grow financial inclusion and increase revenue through innovative alternative data partners. Enhance underwriting accuracy and maximize profitability with alternative data sources. Each participating party uses our desktop application to anonymize, tokenize, and protect all personally identifiable information in their consumer data set within their own local environment. The process generates US-patented crypto-IDs for each anonymized consumer profile locally to enable the matching of mutual consumers across multiple data sets in our secure and neutral Cloud environment. We’re leading the next generation of consumer data.

The Code Ocean Computational Workbench speeds usability, coding and data tool integration, and DevOps and lifecycle tasks by closing technology gaps with a highly intuitive, ready-to-use user experience. Ready-to-use RStudio, Jupyter, Shiny, Terminal, and Git. Choice of popular languages. Access to any size of data and storage type. Configure and generate Docker environments. One-click access to AWS compute resources. Using the Code Ocean Computational Workbench app panel researchers share results by generating and publishing easy-to-use, point-n-click, web analysis apps to teams of scientists without any IT, coding, or using the command line. Create and deploy interactive analysis. Used in standard web browsers. Easy to share and collaborate. Reuseable, easy to manage. Offering an easy-to-use application and repository researchers can quickly organize, publish, and secure project-based Compute Capsules, data assets, and research results.

Betteromics is deployed as a Private SaaS in your VPC so you can draw connections on all your data. Reproducibly validate your structured and unstructured data using configurable rules. Trace and audit your data from input to analysis with complete data provenance. Use natural language processing and large language models to abstract data elements from clinical records for QC, labeling, and analysis. Quickly develop and tune models specific to your task/data: detect anomalies, make predictions, understand your data, and optimize your processes. Enhance and complement your analysis and machine learning with integration-ready public datasets. Clinical-grade security including full encryption, data traceability, and role-based access controls.