Business Software for Databricks

Eureka automatically detects all types and deployments of data stores, understands the data, and identifies your real-time risk. Eureka allows you to choose, customize, and create policies. These policies are automatically translated into platform-specific controls for all your relevant data stores. Eureka constantly compares the real-world implementation with the desired policy. It alerts on gaps and policy drift and recommends risk-prioritized remediations and actions. Know your entire cloud data storage footprint, data store content, security, and compliance risks. With agentless discovery and risk monitoring, you can quickly implement change. Continuously monitor, improve, and communicate cloud data security and compliance. Protect your data and allow you to access it with security measures that do not interfere with business agility or operations. Eureka provides broad visibility, policy and control management as well as continuous monitoring, alerting, and monitoring.

Access data from any location, even within a vast array of diverse environments. The most effective method to boost acquisition and retention is through the enrichment of data and models. By leveraging machine learning, new insights can be uncovered by integrating proprietary models, such as propensity models, with data in a secure manner, which enhances customer profiles and models while allowing for rapid scalability. Enriching data alone is insufficient; your team needs to transition smoothly from insights to actionable strategies. Automate the segmentation of audiences and deploy your campaigns instantly across various channels. Make informed targeting decisions to optimize budget utilization and reduce churn rates. Understand the optimal timing and locations for targeting efforts. Equip yourself with the necessary tools to act on data in real-time. Tracking the complete customer journey, along with the various data types involved, has always posed significant difficulties. With the increasing stringency of privacy regulations and the growing distribution of data, it is now more crucial than ever to ensure secure and straightforward access to those intent signals for effective decision-making, which will ultimately enhance overall operational efficiency.

Enable your offline data to support real-time predictions seamlessly without the need for custom pipelines. Maintain data consistency between offline training and online inference to avoid discrepancies in results. Streamline data engineering processes within a unified framework for better efficiency. Teams can leverage Feast as the cornerstone of their internal machine learning platforms. Feast eliminates the necessity for dedicated infrastructure management, instead opting to utilize existing resources while provisioning new ones when necessary. If you prefer not to use a managed solution, you are prepared to handle your own Feast implementation and maintenance. Your engineering team is equipped to support both the deployment and management of Feast effectively. You aim to create pipelines that convert raw data into features within a different system and seek to integrate with that system. With specific needs in mind, you want to expand functionalities based on an open-source foundation. Additionally, this approach not only enhances your data processing capabilities but also allows for greater flexibility and customization tailored to your unique business requirements.

Access customer information seamlessly from your app database, data warehouses, spreadsheets, or various APIs without the need for coding. Experience a real-time overview of essential customer data directly within platforms like Salesforce, Marketo, HubSpot, and other business systems. Effortlessly consolidate data from multiple sources—be it databases, data warehouses, spreadsheets, or APIs—automatically. You can select specific fields for synchronization, ensuring you receive only the most relevant data. With just a click, integrate your preferred tools into the workflow. Utilize a simple point-and-click interface to transfer necessary data from your databases and spreadsheets to your business applications. This setup empowers your customer success and sales teams by providing them with a comprehensive view of customer data directly within their sales CRM. Benefit from automatic synchronization of information across data warehouses and databases to all your business systems and spreadsheets. Additionally, enjoy the convenience of having all proprietary user and company attributes automatically updated in your CRM. Your support team will also gain immediate access to the vital customer data they require directly from their support system, enhancing overall efficiency and collaboration.

The Wizata Platform enables the manufacturing industry to drive digital transformation. It facilitates the development of AI solutions, from proof of concept to production recommendations, for a complete loop control through AI. This SaaS-Software as a Service platform acts as an orchestrator for your various assets (machines and sensors, AI, edge, etc.) and allows you to easily gather and analyze your data. It is your sole control. You can manage your resources and prioritize your projects based on how your AI solutions solve business problems and improve production processes. We have also developed data science best practices in metalurgics since 2004.

Theom is an advanced cloud data security solution designed to uncover and safeguard all types of data found in cloud storage, APIs, and message queues. Much like a vigilant bodyguard dedicated to protecting valuable assets, Theom ensures that security measures are consistently applied to data, regardless of its storage or access method. By utilizing agentless scanning and natural language processing classifiers, Theom effectively identifies personally identifiable information (PII), protected health information (PHI), financial data, and trade secrets, while accommodating customized taxonomies. Additionally, it reveals dark data—information that remains unused—and shadow data, which has a different security posture compared to its primary version. Theom excels in locating sensitive information, such as developer keys, within APIs and message queues. To assist organizations in prioritizing threats, Theom also assesses the financial impact of data. Furthermore, it maps the intricate relationships between datasets, access identities, and their associated security features, thereby revealing potential vulnerabilities. By illustrating how valuable data is accessed by different identities, such as users and roles, Theom provides a comprehensive view of security attributes, including user location and unusual access patterns. This holistic approach empowers organizations to make informed decisions about their data security strategies.

Enhance the security of your cloud data environment while ensuring your business operations remain efficient. Sentra’s agentless solution can efficiently identify and scan cloud data repositories for sensitive information without hindering performance. By concentrating on the protection of your organization’s most crucial data, Sentra adopts a data-centric methodology. It automatically discovers and evaluates both managed and unmanaged cloud-native data stores. Utilizing a combination of established and bespoke data recognition methods, Sentra effectively pinpoints sensitive information in the cloud. By applying innovative data scanning techniques rooted in intelligent metadata clustering and sampling, users can achieve a dramatic reduction in cloud expenses, significantly outpacing traditional alternatives. The API-first and adaptable classification system offered by Sentra seamlessly connects with your current data catalogs and security infrastructures. Furthermore, you can evaluate potential risks to your data repositories by considering both compliance mandates and your overall security strategies. This comprehensive approach ensures that your security measures are not only effective but also aligned with your business objectives.

Amazon SageMaker Feature Store serves as a comprehensive, fully managed repository specifically designed for the storage, sharing, and management of features utilized in machine learning (ML) models. Features represent the data inputs that are essential during both the training phase and inference process of ML models. For instance, in a music recommendation application, relevant features might encompass song ratings, listening times, and audience demographics. The importance of feature quality cannot be overstated, as it plays a vital role in achieving a model with high accuracy, and various teams often rely on these features repeatedly. Moreover, synchronizing features between offline batch training and real-time inference poses significant challenges. SageMaker Feature Store effectively addresses this issue by offering a secure and cohesive environment that supports feature utilization throughout the entire ML lifecycle. This platform enables users to store, share, and manage features for both training and inference, thereby facilitating their reuse across different ML applications. Additionally, it allows for the ingestion of features from a multitude of data sources, including both streaming and batch inputs such as application logs, service logs, clickstream data, and sensor readings, ensuring versatility and efficiency in feature management. Ultimately, SageMaker Feature Store enhances collaboration and improves model performance across various machine learning projects.

Amazon SageMaker Data Wrangler significantly shortens the data aggregation and preparation timeline for machine learning tasks from several weeks to just minutes. This tool streamlines data preparation and feature engineering, allowing you to execute every phase of the data preparation process—such as data selection, cleansing, exploration, visualization, and large-scale processing—through a unified visual interface. You can effortlessly select data from diverse sources using SQL, enabling rapid imports. Following this, the Data Quality and Insights report serves to automatically assess data integrity and identify issues like duplicate entries and target leakage. With over 300 pre-built data transformations available, SageMaker Data Wrangler allows for quick data modification without the need for coding. After finalizing your data preparation, you can scale the workflow to encompass your complete datasets, facilitating model training, tuning, and deployment in a seamless manner. This comprehensive approach not only enhances efficiency but also empowers users to focus on deriving insights from their data rather than getting bogged down in the preparation phase.

Experience a centralized hub for all your educational and informational needs. Sana is an innovative learning platform powered by AI that equips teams with the ability to discover, disseminate, and leverage the knowledge necessary for fulfilling their objectives. Enhance the learning journey for everyone by merging live collaborative interactions with tailored self-paced courses, all available in a single location. Simplify the sharing of knowledge through the capabilities of Sana Assistant, which can create questions, explanations, images, and even entire courses autonomously. Encourage active participation and excitement through a variety of interactive elements such as quizzes, Q&A sessions, polls, sticky notes, reflection cards, recordings, and much more. Seamlessly integrate Sana with your team's favorite applications, ensuring that your organization's collective knowledge remains accessible and searchable in less than 100 milliseconds. From Github to Google Workspace, Notion, Slack, and Salesforce, whatever you need, Sana is ready to provide insights from it. All of this comes together to foster a vibrant learning culture within your organization.

The platform organizes BI tools and semantic layers, documents data utilizing dbt, and incorporates OpenAI and language models to facilitate self-service advanced analytics. Through TextQL, users without a technical background can effortlessly interact with data by posing queries within their familiar work environments (such as Slack, Teams, or email) and receive prompt and secure automated responses. Additionally, the platform employs NLP and semantic layers, including the dbt Labs semantic layer, to deliver sensible solutions. TextQL enhances the question-to-answer workflow by seamlessly transitioning to human analysts when necessary, significantly streamlining the entire process with AI assistance. At TextQL, we are dedicated to enabling business teams to find the data they need in under a minute. To achieve this goal, we assist data teams in uncovering and creating documentation for their datasets, ensuring that business teams can rely on the accuracy and timeliness of their reports. Ultimately, our commitment to user-friendly data access transforms the way organizations utilize their information resources.

Optable provides a comprehensive data clean room platform designed for seamless activation. This innovative technology empowers both publishers and advertisers to securely strategize, implement, and evaluate their advertising efforts. Representing a new era of data collaboration that prioritizes privacy, Optable enables clients to engage with both their own customers and partners, including those who may not use the platform. Utilizing the platform's Flash Nodes, users can invite external participants into a protected setting. Additionally, Optable features a decentralized identity infrastructure that facilitates the construction of private identity graphs. This setup allows for the creation of purpose-specific, permission-based data clean rooms that significantly reduce data transfer. Ensuring compatibility with data warehouses and other clean rooms is vital to its functionality. Furthermore, by leveraging open-source software, third-party platforms can effectively match their data with Optable's clients and implement secure clean room capabilities tailored to their needs, thereby enhancing the overall efficacy of data collaboration. This multi-faceted approach positions Optable as a leader in the evolving landscape of data privacy and collaboration.

Cutting-edge technology and services are designed to securely transform and elevate sensitive information into actionable insights, thereby fostering innovation and creating new avenues for revenue generation. Through the use of the Mimic synthetic data engine, businesses can effectively synthesize their data assets, ensuring that consumer privacy is safeguarded while preserving the statistical relevance of the information. This synthetic data can be leveraged for a variety of internal initiatives, such as analytics, machine learning, artificial intelligence, marketing efforts, and segmentation strategies, as well as for generating new revenue streams via external data monetization. Mimic facilitates the secure transfer of statistically relevant synthetic data to any cloud platform of your preference, maximizing the utility of your data. In the cloud, enhanced synthetic data—validated for compliance with regulatory and privacy standards—can support analytics, insights, product development, testing, and collaboration with third-party data providers. This dual focus on innovation and compliance ensures that organizations can harness the power of their data without compromising on privacy.

Assisting businesses in actively overseeing their comprehensive data quality lifecycle is achieved through the implementation of contextual data quality assessments, anomaly detection, and corrective measures. By revealing anomalies and relevant metadata, teams are empowered to implement necessary corrective actions effectively. Automated remediation workflows can be initiated to swiftly and efficiently address any errors that arise. This proactive approach helps ensure superior data quality, safeguarding against inaccuracies that could undermine business decision-making. Additionally, the SLA chart offers a detailed overview of service level agreements, showcasing the total number of monitoring activities conducted and any violations encountered. Such insights can significantly aid in pinpointing specific areas of your data that may necessitate further scrutiny or enhancement. Ultimately, maintaining robust data quality is essential for driving informed business strategies and fostering growth.

LlamaIndex serves as a versatile "data framework" designed to assist in the development of applications powered by large language models (LLMs). It enables the integration of semi-structured data from various APIs, including Slack, Salesforce, and Notion. This straightforward yet adaptable framework facilitates the connection of custom data sources to LLMs, enhancing the capabilities of your applications with essential data tools. By linking your existing data formats—such as APIs, PDFs, documents, and SQL databases—you can effectively utilize them within your LLM applications. Furthermore, you can store and index your data for various applications, ensuring seamless integration with downstream vector storage and database services. LlamaIndex also offers a query interface that allows users to input any prompt related to their data, yielding responses that are enriched with knowledge. It allows for the connection of unstructured data sources, including documents, raw text files, PDFs, videos, and images, while also making it simple to incorporate structured data from sources like Excel or SQL. Additionally, LlamaIndex provides methods for organizing your data through indices and graphs, making it more accessible for use with LLMs, thereby enhancing the overall user experience and expanding the potential applications.

Bid farewell to abandoned data catalogs. Acryl Cloud accelerates time-to-value by implementing Shift Left methodologies for data producers and providing an easy-to-navigate interface for data consumers. It enables the continuous monitoring of data quality incidents in real-time, automating anomaly detection to avert disruptions and facilitating swift resolutions when issues arise. With support for both push-based and pull-based metadata ingestion, Acryl Cloud simplifies maintenance, ensuring that information remains reliable, current, and authoritative. Data should be actionable and operational. Move past mere visibility and leverage automated Metadata Tests to consistently reveal data insights and identify new opportunities for enhancement. Additionally, enhance clarity and speed up resolutions with defined asset ownership, automatic detection, streamlined notifications, and temporal lineage for tracing the origins of issues while fostering a culture of proactive data management.

DataGalaxy is redefining how organizations govern and activate their data through a single, collaborative platform built for both business and technical teams. Its data and analytics governance solution provides the visibility, control, and alignment needed to transform data into a true business asset. The platform unites automated data cataloging, AI-driven lineage, and value-based prioritization to ensure every initiative is intentional and measurable. With features like the strategy cockpit and value tracking center, organizations can connect business objectives to actionable data outcomes and monitor ROI in real time. Over 70 native connectors integrate seamlessly with tools like Snowflake, Azure Synapse, Databricks, Power BI, and HubSpot, breaking down data silos across hybrid environments. DataGalaxy also embeds AI-powered assistants and compliance automation for frameworks like GDPR, HIPAA, and SOC 2, making governance intuitive and secure. Trusted by global enterprises including Airbus and Bank of China, the platform is both scalable and enterprise-ready. By blending data discovery, collaboration, and security, DataGalaxy helps organizations move from reactive governance to proactive value creation.

Maintain your usual routine while working within Jupyter Notebooks or any Python setting. Just invoke modelbi.deploy to launch your model, allowing Modelbit to manage it — along with all associated dependencies — in a production environment. Machine learning models deployed via Modelbit can be accessed directly from your data warehouse with the same simplicity as invoking a SQL function. Additionally, they can be accessed as a REST endpoint directly from your application. Modelbit is integrated with your git repository, whether it's GitHub, GitLab, or a custom solution. It supports code review processes, CI/CD pipelines, pull requests, and merge requests, enabling you to incorporate your entire git workflow into your Python machine learning models. This platform offers seamless integration with tools like Hex, DeepNote, Noteable, and others, allowing you to transition your model directly from your preferred cloud notebook into a production setting. If you find managing VPC configurations and IAM roles cumbersome, you can effortlessly redeploy your SageMaker models to Modelbit. Experience immediate advantages from Modelbit's platform utilizing the models you have already developed, and streamline your machine learning deployment process like never before.

The integration of external data represents a pivotal opportunity for businesses to enhance their competitive edge across various sectors, yet many organizations face challenges in navigating the complexities of its implementation. Demyst offers comprehensive tools to assist you in identifying, acquiring, and utilizing the appropriate external data, with our specialists collaborating with you throughout the entire process. You can easily explore and immediately implement data from Demyst’s extensive catalog of sources, or our knowledgeable team can suggest and facilitate the onboarding of new options from any external data provider worldwide. Our certification program for data providers ensures that we thoroughly vet and procure data tailored to your requirements, all under a unified contractual agreement. By eliminating the dilemma of compliance versus speed, Demyst conducts continuous legal, privacy, and security assessments to guarantee that your data access remains both safe and compliant, typically onboarding new data within four weeks or less. Furthermore, Demyst expertly handles the final steps of implementation, allowing you to deploy and monitor the data you require through consistently formatted APIs or files, ensuring a seamless integration into your existing systems. This comprehensive approach streamlines your access to valuable information, empowering your business to thrive in an increasingly data-driven landscape.

Approximately 80% of corporate data is stored in challenging formats such as HTML, PDF, CSV, PNG, and PPTX, among others. Unstructured simplifies the extraction and transformation of intricate data to be compatible with all leading vector databases and LLM frameworks. This platform enables data scientists to preprocess data efficiently at scale, allowing them to allocate more time to modeling and analysis rather than data collection and cleaning. With our enterprise-grade connectors, we can gather data from various sources and convert it into AI-friendly JSON files, making it easier for organizations to integrate AI into their operations. Rely on Unstructured to provide meticulously curated data that is clean of any artifacts and, crucially, ready for use with LLMs. In doing so, we empower businesses to harness the full potential of their data for innovative applications.

Data plays a crucial role in every facet of a processing plant or facility, serving as the backbone for most operational workflows, critical business decisions, and various environmental occurrences. Often, failures can be linked back to this very data, manifesting as operator mistakes, faulty sensors, safety incidents, or inadequate analytics. APERIO steps in to address these challenges effectively. In the realm of Industry 4.0, data integrity stands as a vital component, forming the bedrock for more sophisticated applications, including predictive models, process optimization, and tailored AI solutions. Recognized as the premier provider of dependable and trustworthy data, APERIO DataWise enables organizations to automate the quality assurance of their PI data or digital twins on a continuous and large scale. By guaranteeing validated data throughout the enterprise, businesses can enhance asset reliability significantly. Furthermore, this empowers operators to make informed decisions, fortifies the detection of threats to operational data, and ensures resilience in operations. Additionally, APERIO facilitates precise monitoring and reporting of sustainability metrics, promoting greater accountability and transparency within industrial practices.

With the integration of embedded AI and immersive 3D visualizations, analysts are equipped to formulate groundbreaking business strategies and ensure that no vital insights from their data are overlooked. Virtualitics’ Intelligent Exploration enhances this process by offering AI-assisted exploration that proactively uncovers insights essential for driving impactful decisions. The AI-guided exploration simplifies complex data interpretations into straightforward language, ensuring that every detail is captured. Analysts can delve into a wide array of data types and complexities, swiftly uncovering significant relationships within seconds. Engaging and informative 3D visualizations enhance understanding by vividly portraying data narratives. By utilizing 3D and VR data visualizations, analysts can approach data from fresh perspectives, facilitating the comprehension of intricate findings. Moreover, the ability to share well-annotated insights and clear explanations ensures that all stakeholders are well-informed and aligned with strategic objectives. This holistic approach not only enriches the analysis process but also fosters collaboration among teams.

Kestra is a free, open-source orchestrator based on events that simplifies data operations while improving collaboration between engineers and users. Kestra brings Infrastructure as Code to data pipelines. This allows you to build reliable workflows with confidence. The declarative YAML interface allows anyone who wants to benefit from analytics to participate in the creation of the data pipeline. The UI automatically updates the YAML definition whenever you make changes to a work flow via the UI or an API call. The orchestration logic can be defined in code declaratively, even if certain workflow components are modified.

Organizations are increasingly focused on becoming more data-driven, implementing dashboards, analytics, and data pipelines throughout the contemporary data landscape. However, many organizations face significant challenges with data reliability, which can lead to misguided business decisions and a general mistrust in data that negatively affects their financial performance. Addressing intricate data challenges is often a labor-intensive process that requires collaboration among various teams, all of whom depend on informal knowledge to painstakingly reverse engineer complex data pipelines spanning multiple platforms in order to pinpoint root causes and assess their implications. Pantomath offers a solution as a data pipeline observability and traceability platform designed to streamline data operations. By continuously monitoring datasets and jobs within the enterprise data ecosystem, it provides essential context for complex data pipelines by generating automated cross-platform technical pipeline lineage. This automation not only enhances efficiency but also fosters greater confidence in data-driven decision-making across the organization.

The AI revolution has arrived. The regulatory landscape is constantly changing, and innovation is moving at lightning speed. How can you ensure that your AI systems, as well as those of your vendors, remain compliant, secure, and trustworthy? Cranium helps cybersecurity teams and data scientists understand how AI impacts their systems, data, or services. Secure your organization's AI systems and machine learning systems without disrupting your workflow to ensure compliance and trustworthiness. Protect your AI models from adversarial threats while maintaining the ability to train, test and deploy them.