Best Data Management Software for Amazon Web Services (AWS) - Page 6

Organizations that choose a do-it-yourself method for implementing a graph database should anticipate a timeline of about 2 to 3 months to achieve a production-ready state. In contrast, with Graph Story’s managed services, your operational database can be set up in just minutes. Discover various graph use cases and explore a side-by-side analysis of self-hosting versus managed services. We can accommodate deployments in your existing infrastructure, whether it's on AWS, Azure, or Google Compute Engine, in any geographical location. If you require VPC peering or IP access restrictions, we can easily adapt to your needs. For those looking to create a proof of concept, initiating a single enterprise graph instance only takes a few clicks. Should you need to scale up to a high-availability, production-ready cluster on demand, we are prepared to assist! Our graph database management tools are designed to simplify your experience, allowing you to monitor CPU, memory, and disk usage effortlessly. You also have access to configurations, logs, and the ability to backup your database and restore snapshots whenever necessary. This level of flexibility ensures that your graph database management aligns perfectly with your operational requirements.

Discover tailored solutions for your business through a customized approach that transforms challenges into opportunities, streamlining complex manual processes into seamless intelligent document processing. By harnessing advanced AI technology, we automate business workflows effectively, with Kapture serving as a cloud-based, self-service platform for enterprise-level form extraction. Our AI-driven OCR capabilities simplify the data classification and extraction tasks traditionally requiring significant human effort, catering to a wide range of industries. We efficiently manage forms and images in various formats, including PNG, TIFF, PDF, DOCX, and DOC, ensuring versatility in our handling process. The Kapture platform enables the creation of classifiers, allowing you to categorize different document types, such as invoices, KYC forms, and loan documentation. This systematic organization allows for the efficient separation of composite data into designated classifier folders for further processing. Additionally, our extractor captures vital values from your forms and printed materials with an impressive 80% automation rate, significantly optimizing your workflow. Ultimately, this approach not only enhances efficiency but also empowers your organization to focus on strategic initiatives.

Don't allow concerns about data security or privacy to obstruct your innovation efforts driven by analytics. Dataguise offers robust protection for personal and sensitive information through adaptable masking and encryption solutions, ensuring you can maximize business value. With data sets prepared for analysis delivered in near real-time, you can gain fresher insights and make informed decisions based on a complete understanding of your data landscape. Recognizing the diverse and evolving needs of our customers, Dataguise has built a strong network of carefully selected partners to provide more comprehensive solutions, services, and expertise. This executive guide illustrates how to safeguard data privacy while enhancing data value. When looking at various data discovery solutions, it's clear that Dataguise has a longer history, accommodates a wider array of data types and repositories, achieves lower false-positive rates, and consistently scans data at scale more effectively. By choosing Dataguise, organizations can confidently harness their data to drive decisions that best serve their business objectives, ultimately fostering a culture of informed and strategic decision-making.

Fasoo Data Radar (FDR) is a powerful data discovery and classification solution that enables organizations to locate, analyze, and manage sensitive unstructured data across on-premise servers, cloud storage, and endpoints. By scanning files based on keywords, regex patterns, file formats, and predefined policies, FDR helps organizations maintain control over critical information. With real-time monitoring and centralized policy enforcement, it enhances data security by identifying risks, preventing unauthorized access, and ensuring compliance with regulations like GDPR, HIPAA, and CCPA. FDR seamlessly integrates with enterprise security frameworks, allowing organizations to enforce consistent data protection policies while streamlining operational workflows. By automating data classification and governance, it improves efficiency, strengthens data security, and enhances visibility for regulatory compliance and risk management.

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

Maintain the essence, structure, and accuracy while ensuring confidentiality. Improve data security by anonymizing and altering sensitive information, as well as implementing pseudonymization strategies for adherence to privacy regulations and analytics purposes. The obscured data continues to hold its context and referential integrity, making it suitable for use in testing, analytics, or support scenarios. Serving as an exceptionally scalable and high-performing data masking solution, Informatica Persistent Data Masking protects sensitive information—like credit card details, addresses, and phone numbers—from accidental exposure by generating realistic, anonymized data that can be safely shared both internally and externally. Additionally, this solution minimizes the chances of data breaches in nonproduction settings, enhances the quality of test data, accelerates development processes, and guarantees compliance with various data-privacy laws and guidelines. Ultimately, adopting such robust data masking techniques not only protects sensitive information but also fosters trust and security within organizations.

Elevate your integration capabilities with the most extensive, microservices-oriented, API-centric, and AI-enhanced enterprise iPaaS available. Utilizing the advanced CLAIRE engine, IICS accommodates a wide array of cloud-native integration needs, including data, application, API integration, and Master Data Management (MDM). Our global reach and support for multiple cloud environments extend to major platforms like Microsoft Azure, AWS, Google Cloud Platform, and Snowflake. With unmatched enterprise scalability and a robust security framework backed by numerous certifications, IICS stands as a pillar of trust in the industry. This enterprise iPaaS features a suite of cloud data management solutions designed to boost efficiency while enhancing speed and scalability. Once again, Informatica has been recognized as a Leader in the Gartner 2020 Magic Quadrant for Enterprise iPaaS, reinforcing our commitment to excellence. Experience firsthand insights and testimonials about Informatica Intelligent Cloud Services, and take advantage of our complimentary cloud offerings. Our customers remain our top priority in all facets, including products, services, and support, which is why we've consistently achieved outstanding customer loyalty ratings for over a decade. Join us in redefining integration excellence and discover how we can help transform your business operations.

SQLyog Ultimate serves as a robust solution for MySQL development and administration, allowing database professionals to visually analyze and document schemas while optimizing their structure. This powerful tool offers an automation feature that enables users to schedule data synchronization between two MySQL servers efficiently. Users can easily create job definition files through an interactive wizard, and the tool operates independently of any installation on the MySQL hosts, making it versatile for use with any host. Additionally, SQLyog Ultimate provides an interactive mode for data synchronization, allowing comparisons between source and target data before executing any changes. The user-friendly interface facilitates a detailed examination of data row-by-row, enabling users to make informed decisions on synchronization direction. Furthermore, SQLyog Ultimate also includes capabilities for interactive schema comparison, allowing users to identify differences in tables, indexes, columns, and routines across two databases. This comprehensive functionality makes SQLyog Ultimate an essential asset for any MySQL user looking to enhance their development and administration tasks.

AI teams encounter obstacles that necessitate the development of innovative technologies, which we specialize in creating. Traditional data warehouses and lakes struggle to accommodate unstructured data types such as text, images, and videos. Our approach integrates AI with software development, specifically designed for data scientists, machine learning engineers, and data engineers alike. Instead of reinventing existing solutions, we provide a swift and cost-effective route to bring your projects into production. Your data remains securely stored under your control, and model training occurs on your own infrastructure. By addressing the limitations of current data handling methods, we ensure that AI teams can effectively meet their challenges. Our Studio functions as an extension of platforms like GitHub, GitLab, or BitBucket, allowing seamless integration. You can choose to sign up for our online SaaS version or reach out for an on-premise installation tailored to your needs. This flexibility allows organizations of all sizes to adopt our solutions effectively.

Intel® Tiber™ AI Studio serves as an all-encompassing machine learning operating system designed to streamline and unify the development of artificial intelligence. This robust platform accommodates a diverse array of AI workloads and features a hybrid multi-cloud infrastructure that enhances the speed of ML pipeline creation, model training, and deployment processes. By incorporating native Kubernetes orchestration and a meta-scheduler, Tiber™ AI Studio delivers unparalleled flexibility for managing both on-premises and cloud resources. Furthermore, its scalable MLOps framework empowers data scientists to seamlessly experiment, collaborate, and automate their machine learning workflows, all while promoting efficient and cost-effective resource utilization. This innovative approach not only boosts productivity but also fosters a collaborative environment for teams working on AI projects.

For the first time, it is now possible to capture and retain data attributes such as meaning, usage, lineage, alignment with business outcomes, and ownership, which are often lost after each project, transforming them into valuable knowledge. These essential attributes can be reused effectively to enhance strategic business initiatives that rely on reliable data. By reusing data, you can achieve your objectives more swiftly. Take advantage of the hidden potential within your data to drive success. Unlocking data's potential in relation to your business context can be a game changer. Many of your projects demand similar insights and comprehension of your data, leading to the constant re-creation of the same information. Syniti can provide this critical knowledge at a significantly reduced cost and with improved precision. Rather than discarding your insights, consider unlocking and reapplying the knowledge embedded in your data. By preserving this knowledge, you create a valuable resource for future projects and insights. This approach not only saves time but also enhances overall business intelligence.

The Waylay platform is a modular IoT solution that offers top-tier OEM technology for backend development and operational processes, facilitating the rapid delivery of IoT solutions on a large scale. It features sophisticated rule logic modeling, execution capabilities, and comprehensive lifecycle management. This platform allows for the automation of various data workflows, regardless of their complexity. Designed to seamlessly handle the diverse data patterns found in IoT, OT, and IT, Waylay integrates both streaming and time series analytics into a single, collaborative intelligence environment. By providing non-developer teams with user-friendly, self-service apps focused on key performance indicators, it significantly shortens the time to market for IoT products. Users can identify the most effective automation tools for their specific IoT applications and evaluate them against established benchmarks. Additionally, developing IoT applications diverges significantly from traditional IT development, as it entails connecting the physical realm of Operations Technology, which involves sensors and actuators, with the digital landscape of Information Technology, encompassing databases and software systems. This bridging of worlds highlights the unique challenges and opportunities presented by IoT application development.

Efficiently scan and catalog metadata, uncover and characterize data, while offering comprehensive lineage tracking over millions of datasets. Organize and classify data assets across diverse environments to enhance their value and facilitate reuse. Perform automated scanning across multi-cloud environments, business intelligence tools, ETL processes, and external metadata catalogs, along with various data types. Utilize AI-driven capabilities for domain discovery, data similarity assessment, business term linkages, and tailored recommendations. Monitor data movement with precision, ranging from overarching system perspectives to detailed column-level lineage, accompanied by thorough impact assessments. Access the Data Asset Analytics dashboard to gain insights into asset utilization, enrichment processes, and collaborative efforts. Examine data quality protocols, scorecards, metric clusters, and profiling statistics within their relevant contexts. Engage with shared data intelligence through certifications, ratings and feedback, a Q&A feature, and timely change alerts. What truly distinguishes Informatica is its extensive and robust suite of enterprise-grade data management solutions, ensuring comprehensive support for diverse data needs. With such capabilities, organizations can navigate their data landscapes more effectively and make informed decisions.

Enhance the potential of both structured and unstructured data within your organization by leveraging outstanding features for data integration, quality enhancement, and cleansing. The SAP Data Services software elevates data quality throughout the organization, ensuring that the information management layer of SAP’s Business Technology Platform provides reliable, relevant, and timely data that can lead to improved business results. By transforming your data into a dependable and always accessible resource for insights, you can optimize workflows and boost efficiency significantly. Achieve a holistic understanding of your information by accessing data from various sources and in any size, which helps in uncovering the true value hidden within your data. Enhance decision-making and operational effectiveness by standardizing and matching datasets to minimize duplicates, uncover relationships, and proactively address quality concerns. Additionally, consolidate vital data across on-premises systems, cloud environments, or Big Data platforms using user-friendly tools designed to simplify this process. This comprehensive approach not only streamlines data management but also empowers your organization to make informed strategic choices.

Data management software is predominantly utilized by enterprise business teams, necessitating a design that prioritizes user-friendliness, automation, and intelligence. Furthermore, it is essential for the software to comply with a variety of industry-specific regulations and data protection mandates. To ensure that business teams can make informed, data-driven strategic decisions, the data must maintain standards of adequacy, accuracy, consistency, high quality, and secure accessibility. The software promotes an integrated methodology for managing data privacy, ensuring data quality, overseeing test data management, facilitating data analytics, and supporting data modeling. Additionally, it effectively manages escalating data volumes through a service engine-based architecture, while also addressing specialized data processing needs beyond standard functionalities via a user-defined function framework and Python adapter. Moreover, it establishes a streamlined governance framework that focuses on data privacy and quality management, enhancing overall data integrity. As a result, organizations can confidently rely on this software to support their evolving data requirements.

Revamp your applications to ensure they adhere to local compliance and security standards. Align your control measures and enhance your compliance framework while still utilizing the benefits of the cloud. Allow your customized applications to satisfy data residency mandates with little to no additional development effort. Expand into new markets and boost your revenue without compromising your customers' experience. The InCountry platform guarantees that your financial services applications remain compliant with data regulations across multiple countries, enabling you to maximize their potential. Safeguard your journey towards precision medicine with an advanced data compliance solution. Speed up research initiatives and reduce the time to discovery with healthcare-centric offerings from InCountry. Seamlessly enter new markets and generate revenue while maintaining an uninterrupted customer experience. Additionally, the InCountry platform ensures that your sales operations consistently align with local data regulations, fostering trust and reliability.

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

Data forms the essential foundation of the digital economy, and we are transforming the way organizations utilize data to generate value. Enterprises rely on Enveil’s award-winning ZeroReveal® solutions to securely and privately handle data in situ across various organizational borders, jurisdictions, and third-party interactions, all while maintaining the confidentiality of both the data and the outcomes. Our privacy-enhancing technologies (PETs), coupled with homomorphic encryption, create an effective and decentralized framework for data collaboration that aims to minimize risks and tackle business issues such as data sharing, monetization, and regulatory compliance. By safeguarding data during its use and processing—often regarded as the 'holy grail' of secure data handling—we offer the most advanced encrypted search, analytics, and machine learning products available. Enveil stands as a trailblazer in privacy-enhancing technology, dedicated to ensuring secure data usage, sharing, and monetization, while continuously pushing the boundaries of what is possible in data protection. As the digital landscape evolves, our solutions are poised to adapt and meet emerging challenges in data security and privacy.

Transforming data and conducting marketing analysis for enterprises is crucial for instilling assurance in your marketing investments and maximizing returns on advertising expenditures. Poorly managed unstructured data can jeopardize marketing decisions, making it essential to extract, transform, and load your data efficiently to execute marketing initiatives confidently. By utilizing anaticsTM, you can connect and centralize your marketing data for streamlined access. Meaningfully load, normalize, and transform your data to enable comprehensive analysis and performance tracking. Gather, prepare, and scrutinize all your marketing information effortlessly, eliminating the tedious task of manually extracting data from various platforms. With fully automated data integration from over 400 sources, you can effortlessly export your data to preferred destinations. Secure your raw data in the cloud, ensuring you can access it whenever needed, while also reinforcing your marketing strategies with reliable data. Direct your focus towards actionable growth rather than the cumbersome process of downloading numerous spreadsheets and CSV files, allowing for a more efficient allocation of resources. Embrace this transformative approach to marketing data management and watch your business thrive.

We aim to relieve ML engineers from the burdens of data engineering so they can concentrate on their passion for developing superior models more efficiently. Our innovative product serves as a robust framework that simplifies and accelerates the process for developers to discover, comprehend, and disseminate visual data on a large scale, making it ten times easier. Users can automatically generate custom interval attributes using pre-trained extractors or any model of their choice, enhancing the flexibility of data manipulation. The platform allows for effective data visualization and the analysis of model performance by leveraging custom attributes alongside standard KPIs. This functionality enables users to query data, identify rare edge cases, and curate new training datasets across their entire data lake with ease. Additionally, it facilitates the seamless saving, editing, versioning, commenting, and sharing of frames, sequences, or objects with both colleagues and external partners. SiaSearch stands out as a data management solution that automatically extracts frame-level contextual metadata, streamlining fast data exploration, selection, and evaluation. By automating these processes with intelligent metadata, engineering productivity can more than double, effectively alleviating bottlenecks in the development of industrial AI. Ultimately, this allows teams to innovate more rapidly and efficiently in their machine learning endeavors.

Since its emergence in 2010, Hadoop has established itself as a crucial component of the data management ecosystem. Throughout the past decade, a significant number of organizations have embraced Hadoop to enhance their data lake frameworks. While Hadoop provided a budget-friendly option for storing vast quantities of data in a distributed manner, it also brought forth several complications. Operating these systems demanded specialized IT skills, and the limitations of on-premises setups hindered the ability to scale according to fluctuating usage requirements. The intricacies of managing these on-premises Hadoop configurations and the associated flexibility challenges are more effectively resolved through cloud solutions. To alleviate potential risks and costs tied to data modernization initiatives, numerous businesses have opted to streamline their cloud data migration processes with WANdisco. Their LiveData Migrator serves as a completely self-service tool, eliminating the need for any WANdisco expertise or support. This approach not only simplifies migration but also empowers organizations to handle their data transitions with greater efficiency.

Promethium empowers data and analytics teams to enhance their efficiency, enabling them to keep pace with the increasing volumes of data and the evolving demands of the business landscape. Merely linking to a data warehouse or lake for raw data access falls short of meeting the required standards. The process of refining datasets demands considerable effort from data teams, which are not expanding at the same rate as the influx of data or the appetite for insights. By leveraging Promethium, burdened data teams can optimize their workflows, leading to faster deliveries. The platform minimizes reliance on traditional ETL processes, granting on-demand access to data in its original location. This reduction in data movement not only conserves time but also cuts costs. With Promethium, an individual can achieve in mere minutes what generally requires a team several months and multiple tools to accomplish. Users can effortlessly connect and catalog data sources, as well as create and query cross-source datasets with just a few clicks, all without needing to write any code. This significant decrease in custom coding and ETL processes allows for real-time validation of data accuracy, eliminating the delays often associated with extensive ETL efforts. Additionally, the ability to instantly share completed work fosters a culture of reuse, preventing the need for repetitive recreation of analyses. Such features not only streamline operations but also enhance collaboration among team members.

The Qlik Data Integration platform designed for managed data lakes streamlines the delivery of consistently updated, reliable, and trusted data sets for business analytics purposes. Data engineers enjoy the flexibility to swiftly incorporate new data sources, ensuring effective management at every stage of the data lake pipeline, which includes real-time data ingestion, refinement, provisioning, and governance. It serves as an intuitive and comprehensive solution for the ongoing ingestion of enterprise data into widely-used data lakes in real-time. Employing a model-driven strategy, it facilitates the rapid design, construction, and management of data lakes, whether on-premises or in the cloud. Furthermore, it provides a sophisticated enterprise-scale data catalog that enables secure sharing of all derived data sets with business users, thereby enhancing collaboration and data-driven decision-making across the organization. This comprehensive approach not only optimizes data management but also empowers users by making valuable insights readily accessible.

SAS Visual Statistics allows for collaborative data exploration among multiple users, enabling them to interactively develop and refine predictive models. Data scientists and statisticians can leverage the most suitable analytical techniques to act on insights at a detailed level. Consequently, you will discover insights at remarkable speeds, uncovering new opportunities for revenue growth. The platform facilitates the construction and fine-tuning of models aimed at specific demographics or segments while simultaneously running various scenarios. This capability encourages users to pose numerous what-if questions to enhance outcomes. Additionally, results can be operationalized through automatically generated score code. Users are empowered to visually manipulate data by adding or adjusting variables, eliminating outliers, and more. Changes can be instantly assessed for their impact on the model's predictive accuracy, allowing for swift adjustments. Data science teams enjoy the ultimate flexibility by working in their preferred programming languages, maximizing their expertise. Ultimately, SAS Visual Statistics integrates all analytical resources, making it a comprehensive solution for data-driven decision-making. It fosters an environment where innovation can thrive, pushing the boundaries of what data analysis can achieve.

SAS® Viya® offers a robust and scalable analytics platform that is both efficient and easy to implement, allowing organizations to address a variety of business challenges. The insights generated automatically help in pinpointing the most frequently used variables across all models, highlighting key variables selected along with evaluation outcomes for each model. With the integration of natural language generation, project summaries are produced in straightforward language, which simplifies the interpretation of reports for users. Moreover, members of the analytics team can enhance the insights report with project notes, promoting better communication and teamwork. SAS further enables the integration of open source code within analyses, allowing users to utilize open source algorithms effortlessly in its platform. This flexibility encourages collaboration throughout your organization, as users are free to program in their preferred language. Additionally, you can leverage SAS Deep Learning with Python (DLPy), an open-source package available on GitHub, to expand your analytical capabilities even further. By using these tools, businesses can significantly enhance their data-driven decision-making processes.