Best Data Management Software for Small Business - Page 70

The early bird gets the sale. Filter, match and route leads to the right salesperson instantaneously. Close more deals. LeadAngel is a B2B Lead Management platform, including Lead to Account Matching and Routing. Fast, Reliable, and Customizable Operations works with Salesforce CRM and others. APIs available to route and match leads. LeadAngel helps businesses, organizations, and enterprises to improve sales process to close more deals, faster. The software offers lead routing, lead matching, fuzzy matching, lead deduplication, account based marketing strategies and detailed reporting. Matching is very customizable and extremely fast. Our system can identify matching companies in dozens of ways. You can further optimize your sales funnel by using tools like auto-conversion of leads to contacts if you find a matching account.

Oracle SQL Developer Data Modeler is a complimentary graphical application designed to boost efficiency and streamline the process of data modeling. With this tool, users can effortlessly create, navigate, and modify various models, including logical, relational, physical, multi-dimensional, and data type models. The Data Modeler also offers capabilities for both forward and reverse engineering, while facilitating collaborative efforts through built-in source code management. It is versatile enough to be utilized in traditional setups as well as cloud-based environments. As part of the Oracle Database Tools suite, Oracle SQL Developer Data Modeler stands out as a comprehensive, independent product featuring a wide array of data and database modeling tools and utilities. Additional resources, including a general FAQ and other relevant materials, can be found on the Data Modeler homepage. This document aims to address some of the pricing-related inquiries that have emerged within the community, providing helpful insights for users navigating these questions.

DTM Data Modeler serves as a CASE tool designed for database developers, facilitating both forward and reverse engineering processes. This user-friendly application allows for the manipulation of both logical and physical data models, visualized through entity-relationship diagrams. Aimed at database architects and developers, it connects seamlessly with data sources through the ODBC interface, ensuring compatibility with contemporary database management systems. In addition to managing fundamental model properties, such as entities and their interrelationships, the software enables the creation of indexes and triggers at the physical level that align with the modeled database tables. The feature for foreign key migration enhances schema development by providing a more intuitive and visual approach, while also minimizing the risk of integrity errors within the model. Furthermore, users can generate database schema objects directly in the database or produce SQL scripts that reflect the model and adhere to custom user-defined settings, making the entire process more efficient and streamlined. Overall, DTM Data Modeler equips developers with a robust set of tools for effective database design and management.

Visualize and comprehend database architectures while recognizing their interconnections. Develop robust logical and physical data models with precision. Reverse engineer current database frameworks to represent them visually in diagrams. Produce comprehensive reports in formats such as HTML, RTF, or PDF. Efficiently construct quality database designs or implement modifications to existing models automatically, supplying documentation across various platforms. Create intricate logical and physical entity-relationship models and facilitate both reverse and forward engineering of databases seamlessly. Connect to numerous databases natively and concurrently, including Oracle, SAP, MySQL, SQL Server, PostgreSQL, DB2, Ingres, and Microsoft Access. Maintain synchronization between models and existing databases through Change Script Generations and the Update Model functionalities. Effortlessly convert data architectures from one database platform to another, aiding in business migration efforts. Additionally, generate extensive hyperlinked reports detailing existing database structures in various formats, enhancing accessibility and usability. This comprehensive approach ensures a well-rounded understanding and efficient management of database systems.

Illustrate Sequelize models, their fields, and associations in a visual format to enhance understanding. By incorporating annotations, comments, images, and hyperlinks into your diagrams, you can create visually appealing representations that are also suitable for printing. These diagrams serve as a detailed map of your data architecture, enabling you to identify mistakes easily. Think of it as a blueprint for a house; it provides clarity on what you are constructing, how different elements are interconnected, and includes essential documentation. This visual tool aids all team members and clients in grasping the relationships between collections and documents effectively. Additionally, it allows for the design of database structures and the generation of corresponding code, minimizing errors and facilitating swift modifications. With these diagrams, you not only streamline your development process but also enhance collaboration and communication within your team.

The software is fully compatible with the UML 2.X standard metamodel, accommodating a variety of diagrams including class, object, use case, component, deployment, composite structure, sequence, communication, statechart, activity, timing, interaction overflow, information flow, and profile diagrams. In addition to UML, it also facilitates modeling with SysML diagrams such as requirement, block definition, internal block, and parametric diagrams. It is optimized for Retina (High-DPI) displays, ensuring that all diagrams, text, and icons appear exceptionally sharp and can be easily exported as High-DPI images in formats like PNG and JPEG. Users can effortlessly discover and install numerous third-party extensions, many of which are open source and available on GitHub. The tool also incorporates a range of shorthands in the Quick Edit feature, allowing for the swift creation of elements and relationships simultaneously, including sub-classes and supporting interfaces, thus enhancing overall productivity. Additionally, this versatility makes it an invaluable resource for professionals seeking comprehensive modeling capabilities.

WinPure™ MDM provides a comprehensive master data management solution tailored to your business needs, enabling a unified view of your data through a variety of features designed to enhance data management. Its offerings are a mix of options sourced from the clean & match enterprise edition, specifically adapted for straightforward web-based data preparation and MDM processes. Users can handle data in various formats and leverage numerous effective methods to clean, standardize, and transform that data. The solution incorporates leading-edge data matching and error-tolerant technologies alongside an easily configurable survivorship mechanism. Key advantages include reduced costs and expedited time to market, along with user-friendly interfaces that require minimal training and implementation efforts. This results in enhanced business outcomes and quicker deployment of MDM systems or other technologies. Additionally, it supports faster and more precise batch loading, along with intuitive data preparation tools. The platform also offers flexible and efficient connectivity with various internal and external databases and systems through its API, facilitating quicker realization of synergies during mergers and acquisitions. Overall, WinPure™ MDM not only streamlines data management but also enhances organizational agility in responding to dynamic market demands.

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.

Streamlining the entry of order and invoice data from PDFs into ERP systems is what PDF-Mapper excels at, making it an ideal choice for organizations striving for excellence in document processing. Gone are the days of manually inputting data, as PDF-Mapper automates this task with remarkable speed and precision. This innovative tool boasts a commitment to 100% accuracy, ensuring that all necessary information from each PDF document is reliably captured and processed. With its built-in automatic validation feature, PDF-Mapper proactively notifies users of any discrepancies in incoming orders and invoices before the data is uploaded to the system. Companies that adopt PDF-Mapper elevate their order and invoice processing to new heights, significantly enhancing productivity and efficiency. By simplifying integration with recurring customers and suppliers, PDF-Mapper optimizes the entire PDF data entry workflow. Furthermore, as an on-premise solution, PDF-Mapper guarantees that your data remains secure and under your control, being installed locally at your facility. This level of security adds an additional layer of confidence for businesses looking to modernize their document handling processes.

TimescaleDB brings the power of PostgreSQL to time-series and event data at any scale. It extends standard Postgres with features like automatic time-based partitioning (hypertables), incremental materialized views, and native time-series functions, making it the most efficient way to handle analytical workloads. Designed for use cases like IoT, DevOps monitoring, crypto markets, and real-time analytics, it ingests millions of rows per second while maintaining sub-second query speeds. Developers can run complex time-based queries, joins, and aggregations using familiar SQL syntax — no new language or database model required. Built-in compression ensures long-term data retention without high storage costs, and automated data management handles rollups and retention policies effortlessly. Its hybrid storage architecture merges row-based performance for live data with columnar efficiency for historical queries. Open-source and 100% PostgreSQL compatible, TimescaleDB integrates with Kafka, S3, and the entire Postgres ecosystem. Trusted by global enterprises, it delivers the performance of a purpose-built time-series system without sacrificing Postgres reliability or flexibility.

Experience a revolutionary blend of AI-driven data analytics and engaging storytelling in real-time. Say goodbye to cumbersome, outdated dashboards and traditional Q&A setups. Anna functions like a human collaborator, streamlining analysis and uncovering insights, ultimately saving you valuable time while empowering you to discover game-changing revelations buried within your data. Hyper Anna's AI-enhanced insights rapidly analyze millions of data points, providing your team with timely notifications about crucial changes, including what has shifted, when it happened, the reasons behind these changes, and the extent of their impact. This innovative tool takes the burden off tasks such as writing SQL queries, crafting visual representations, generating headlines, and even establishing alerts and scheduled reports. Hyper Anna not only delivers clear insights but also facilitates a collaborative environment for your team to communicate effectively, tackle challenges, and seize new opportunities. Furthermore, it seamlessly integrates with any ODBC-compatible database, allowing for secure connections to your existing data with minimal preparation or the option to upload flat files directly. By leveraging Hyper Anna, organizations can transform their approach to data and make informed decisions more efficiently than ever before.

Cortex is an innovative open-source solution that enhances horizontal scalability. While Prometheus is capable of handling up to 1 million samples per second on a single machine, Cortex enables a virtually limitless level of horizontal scaling. In an ever-evolving landscape, it is essential to adopt alternative strategies for monitoring individual virtual machines or servers. Prometheus features a service-discovery-driven, pull-based metrics system that caters to the dynamic characteristics of microservices. This capability allows for seamless monitoring of your entire ecosystem, regardless of the number of components involved. You can instrument your application to generate tailored metrics using the standard Prometheus client libraries, or you can leverage the vast array of Prometheus Exporters that gather data from existing software like MySQL, Redis, Java, ElasticSearch, and many others. By adopting these tools, organizations can ensure they maintain visibility and control over their complex infrastructures. This flexibility is particularly valuable in today's fast-paced, continuously changing technological environments.

Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.

Azure Time Series Insights Gen2 is a robust and scalable IoT analytics service that provides an exceptional user experience along with comprehensive APIs for seamless integration into your current workflow or application. This platform enables the collection, processing, storage, querying, and visualization of data at an Internet of Things (IoT) scale, ensuring that the data is highly contextualized and specifically tailored for time series analysis. With a focus on ad hoc data exploration and operational analysis, it empowers users to identify hidden trends, detect anomalies, and perform root-cause investigations. Furthermore, Azure Time Series Insights Gen2 stands out as an open and adaptable solution that caters to the diverse needs of industrial IoT deployments, making it an invaluable tool for organizations looking to harness the power of their data. By leveraging its capabilities, businesses can gain deeper insights into their operations and make informed decisions to drive efficiency and innovation.

The HyperSense platform is a cloud-native, SaaS-based augmented analytics solution designed to assist enterprises in making quicker and more informed decisions by utilizing Artificial Intelligence (AI) throughout the data value chain. It seamlessly integrates data from various sources, generates insights by developing, interpreting, and refining AI models, and disseminates these insights organization-wide. Acting as a comprehensive solution, HyperSense accelerates decision-making in telecom enterprises through its self-service AI capabilities. With its no-code interface, the platform is user-friendly and quick to set up, enabling business users, domain specialists, and data scientists to collaboratively create and manage AI models across the entire organization. This innovative approach not only enhances operational efficiency but also fosters a data-driven culture in the workplace.

Apache Traffic Server™ is a high-performance, scalable, and flexible caching proxy server that supports both HTTP/1.1 and HTTP/2 protocols. Originally developed as a commercial product, it was later contributed to the Apache Foundation by Yahoo!, and is now widely utilized by numerous prominent content delivery networks (CDNs) and content providers. By caching and reusing frequently accessed web pages, images, and web service calls, it enhances response times while minimizing server load and bandwidth consumption. The server is designed to efficiently scale on contemporary symmetric multiprocessing (SMP) hardware, capable of managing tens of thousands of requests each second. Users can easily implement features like keep-alive, content filtering or anonymization, and load balancing by integrating a proxy layer. Additionally, it offers APIs that allow for the development of custom plug-ins, enabling modifications to HTTP headers, managing Edge Side Includes (ESI) requests, or even creating unique caching algorithms. With its ability to process over 400TB of data daily at Yahoo! in both forward and reverse proxy configurations, Apache Traffic Server stands out as a robust and reliable solution for high-traffic environments. Its proven track record makes it an ideal choice for organizations looking to enhance their web infrastructure efficiency.

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.

Miuros transforms your data into practical insights using AI-driven analytics, quality assurance, and automation tailored for expanding customer service teams across the globe. With a treasure trove of customer service data at your disposal, we are here to help you extract its full potential. The Miuros Intelligence Suite enables you to quickly address complex inquiries, enhance customer experiences, and boost operational efficiency. Our adaptable dashboards empower managers to make informed, fair decisions independently based on data. Additionally, our quality assurance solution focuses on providing agents with opportunities for growth and improvement. For more established customer service teams, we offer an AI-powered assistant that leverages machine learning to handle repetitive tasks, allowing your team to focus on higher-level issues. Furthermore, our customer service data suite seamlessly integrates with platforms like Zendesk, Freshdesk, Salesforce Service Cloud, and Help Scout, ensuring you have comprehensive oversight of your customer service processes. We will handle the setup of your customer service data suite, eliminating the need for your IT department's involvement, so you can focus on what truly matters—enhancing service quality and customer satisfaction.

Oracle Cloud Infrastructure (OCI) Data Flow is a comprehensive managed service for Apache Spark, enabling users to execute processing tasks on enormous data sets without the burden of deploying or managing infrastructure. This capability accelerates the delivery of applications, allowing developers to concentrate on building their apps rather than dealing with infrastructure concerns. OCI Data Flow autonomously manages the provisioning of infrastructure, network configurations, and dismantling after Spark jobs finish. It also oversees storage and security, significantly reducing the effort needed to create and maintain Spark applications for large-scale data analysis. Furthermore, with OCI Data Flow, there are no clusters that require installation, patching, or upgrading, which translates to both time savings and reduced operational expenses for various projects. Each Spark job is executed using private dedicated resources, which removes the necessity for prior capacity planning. Consequently, organizations benefit from a pay-as-you-go model, only incurring costs for the infrastructure resources utilized during the execution of Spark jobs. This innovative approach not only streamlines the process but also enhances scalability and flexibility for data-driven applications.

HeatWave is a powerful, highly parallel in-memory query accelerator designed for Oracle MySQL Database Service, significantly boosting MySQL performance for both analytics and mixed workloads. It outperforms Amazon Redshift by a factor of 6.5 at just half the cost, surpasses Snowflake by 7 times while costing one-fifth as much, and is 1400 times quicker than Amazon Aurora at half the expense. This service uniquely facilitates the execution of OLTP and OLAP tasks directly within the MySQL database, thereby eliminating the challenges and costs associated with transferring and integrating data with an external analytics platform. The innovative MySQL Autopilot leverages cutting-edge machine-learning methods to streamline HeatWave’s functionality, enhancing usability, performance, and scalability even further. Additionally, HeatWave is specifically optimized for use within Oracle Cloud Infrastructure (OCI), ensuring seamless integration and efficiency. As a result, users can enjoy a comprehensive solution that meets diverse analytical needs without the usual complexities.

The Streaming service is a real-time, serverless platform for event streaming that is compatible with Apache Kafka, designed specifically for developers and data scientists. It is seamlessly integrated with Oracle Cloud Infrastructure (OCI), Database, GoldenGate, and Integration Cloud. Furthermore, the service offers ready-made integrations with numerous third-party products spanning various categories, including DevOps, databases, big data, and SaaS applications. Data engineers can effortlessly establish and manage extensive big data pipelines. Oracle takes care of all aspects of infrastructure and platform management for event streaming, which encompasses provisioning, scaling, and applying security updates. Additionally, by utilizing consumer groups, Streaming effectively manages state for thousands of consumers, making it easier for developers to create applications that can scale efficiently. This comprehensive approach not only streamlines the development process but also enhances overall operational efficiency.

Easily create and execute highly parallel data transformation and processing tasks using U-SQL, R, Python, and .NET across vast amounts of data. With no need to manage infrastructure, you can process data on demand, scale up instantly, and incur costs only per job. Azure Data Lake Analytics allows you to complete big data tasks in mere seconds. There’s no infrastructure to manage since there are no servers, virtual machines, or clusters that require monitoring or tuning. You can quickly adjust the processing capacity, measured in Azure Data Lake Analytics Units (AU), from one to thousands for every job. Payment is based solely on the processing used for each job. Take advantage of optimized data virtualization for your relational sources like Azure SQL Database and Azure Synapse Analytics. Your queries benefit from automatic optimization, as processing is performed close to the source data without requiring data movement, thereby enhancing performance and reducing latency. Additionally, this setup enables organizations to efficiently utilize their data resources and respond swiftly to analytical needs.

From Low to High-Volume Scanning and Automation, CapturePoint serves as a front-end system that can greatly enhance the invoice processing workflow. In larger organizations with extensive accounts payable teams, this could mean the difference between needing to hire more specialized staff or achieving greater productivity and lowering costs through efficiency improvements. Given the immense volume of documentation in the healthcare sector, having an effective and streamlined system is essential for managing everything from patient data to HIPAA compliance documents and medical notes. Ademero’s Document Scanning Software systems have emerged as the preferred choice for the modern healthcare industry. In addition to automatically recognizing various document types within the extensive legal paperwork that requires proper identification of matter numbers and alignment with the correct case files, CapturePoint is capable of managing employment applications, health insurance claims, tax documents, and numerous internal records. This versatility allows organizations to minimize errors and maximize their operational efficiency.

Concentrate on producing insightful and impactful reports and analytics rather than getting bogged down in the complexities of data warehouse code. Avoid allowing your data warehouse to turn into a chaotic mix of numerous difficult-to-manage pipelines, notebooks, stored procedures, tables, and views. Dimodelo DW Studio significantly minimizes the workload associated with designing, constructing, deploying, and operating a data warehouse. It enables the design and deployment of a data warehouse optimized for Azure Synapse Analytics. By creating a best practice architecture that incorporates Azure Data Lake, Polybase, and Azure Synapse Analytics, Dimodelo Data Warehouse Studio ensures the delivery of a high-performance and contemporary data warehouse in the cloud. Moreover, with its use of parallel bulk loads and in-memory tables, Dimodelo Data Warehouse Studio offers an efficient solution for modern data warehousing needs, enabling teams to focus on valuable insights rather than maintenance tasks.