Best Big Data Platforms for Startups - Page 7

Edge 226 is a global provider data-driven tech solutions. It focuses on providing its clients smart tools for quality and transparent user acquisition. Peak DSP is Edge's most popular product. It is a Performance-Driven DSP which enables programmatic buying to ensure quality user acquisition and retention. Peak DSP offers: * An AI-driven algorithm that optimizes and predicts install & follow-up events: registrations. Subscriptions. Purchases. Or any other action * Data-based targeting using Lookalike Audiences, Extern User Data and Audience Match * Direct integrations Apps owned & operated by the company. Mobile device manufacturers & carrier-based supply More than 35 of the top SSPs in the world * All verticals, all environments: Gaming, shopping and utilities, as well as sports (etc. Campaigns available on desktop, mobile web, and in-app * Multiple creative types available: Rewarded video Playable ads Banners, native ads and text ads HTML/Rich Media JavaScript tags

MX empowers financial institutions and fintech companies to leverage their data in a way that allows them to excel in a swiftly changing sector. Our innovative solutions facilitate the rapid and straightforward collection, enhancement, analysis, presentation, and application of financial data for our clients. By placing a user’s data front and center, MX transforms it into clear, unified, and engaging visual representations. Consequently, users become more engaged and involved with your digital banking offerings. The Helios cross-platform framework equips MX clients with the capability to deliver mobile banking services across various platforms and devices, all constructed from a single C++ codebase. This significantly reduces maintenance expenses and fosters a more agile development approach, ultimately enhancing the overall user experience in digital banking. With these advancements, financial institutions can stay ahead of the curve and better meet the demands of their customers.

Sigma is a cloud-based business intelligence (BI), and analytics application. Sigma is trusted by data-first businesses. It provides live access to cloud data warehouses via an intuitive spreadsheet interface. This allows business experts to get more information about their data without having to write a single line code. Business users can access their data in real-time using the cloud's full power and familiar interface. Sigma is self-service analytics at its best.

Transform your business with the capabilities of a vast team of data scientists and analysts at your fingertips. Our AI-driven analytics platform is designed for ease of use and accessibility, allowing anyone to interpret complex data effortlessly. Instead of merely dedicating your time to gathering and analyzing past data, shift your focus towards crafting compelling narratives that guide future actions. With Pickaxe, everything is streamlined for you in real-time, featuring AI-enhanced dashboards and profound human insights. While your data platform may reveal ‘what’ is occurring, it should also provide clarity on ‘so what’ and ‘now what’ to drive informed decision-making. By leveraging these insights, you can elevate your strategic initiatives and respond proactively to emerging opportunities.

Ignite your creativity with unparalleled Points-of-Interest (POI) data, comprehensive business listings, and insights into store visitor behavior across the United States. This extensive dataset features approximately 5 million POIs, encompassing every venue where consumers spend their money, including prominent retail chains, shopping centers, convenience stores, airports, and more. Additionally, it provides analytics on store visits, foot traffic statistics, and demographic insights related to POIs. The data can address critical questions such as the frequency of visits to stores, the origins of visitors, and their other shopping preferences. Effortlessly merge your current POI information with SafeGraph's enhanced Places data, which includes details like business categories, operating hours, visitation counts, and peak times. More than 5,000 leading brands are mapped to over 1 million points of interest, ensuring a comprehensive view. Locations that generate noise, such as ATMs and Red Box kiosks, are excluded from the dataset, as are closed businesses and irrelevant entities like home-based LLCs lacking employees. This meticulous curation guarantees that you receive only the most relevant and actionable insights for your commercial endeavors.

BryteFlow creates remarkably efficient automated analytics environments that redefine data processing. By transforming Amazon S3 into a powerful analytics platform, it skillfully utilizes the AWS ecosystem to provide rapid data delivery. It works seamlessly alongside AWS Lake Formation and automates the Modern Data Architecture, enhancing both performance and productivity. Users can achieve full automation in data ingestion effortlessly through BryteFlow Ingest’s intuitive point-and-click interface, while BryteFlow XL Ingest is particularly effective for the initial ingestion of very large datasets, all without the need for any coding. Moreover, BryteFlow Blend allows users to integrate and transform data from diverse sources such as Oracle, SQL Server, Salesforce, and SAP, preparing it for advanced analytics and machine learning applications. With BryteFlow TruData, the reconciliation process between the source and destination data occurs continuously or at a user-defined frequency, ensuring data integrity. If any discrepancies or missing information arise, users receive timely alerts, enabling them to address issues swiftly, thus maintaining a smooth data flow. This comprehensive suite of tools ensures that businesses can operate with confidence in their data's accuracy and accessibility.

Experience immediate advantages for your business right after installation. Discover the functionality of our system, which stands out as the quickest and most user-friendly solution for evaluating extensive geographically dispersed data. This innovative method of analytics breaks free from the limitations typically found in conventional big data warehouses, database designs, and edge computing frameworks. Gain insights into the platform's features that facilitate centralized management and control, streamline automated software setup and orchestration, and support data input and storage across diverse geographic locations. By adopting this new approach, you can enhance your data capabilities and drive growth more effectively than ever before.

A new category of AI. Most AI solutions today are designed using a mathematical and statistical lens. We took a different approach. Intelligent Artifacts' team has created a new type of AI based on information theory. It is a true AGI that eliminates the current shortcomings in machine intelligence. Our framework separates the intelligence layer from the data and application layers, allowing it to learn in real time and allowing it to make predictions down to the root cause. A truly integrated platform is required for AGI. Intelligent Artifacts will allow you to model information, not data. Predictions and decisions can be made across multiple domains without the need for rewriting code. Our dynamic platform and specialized AI consultants will provide you with a tailored solution that quickly provides deep insights and better outcomes from your data.

HEAVY.AI is a pioneer in accelerated analysis. The HEAVY.AI platform can be used by government and business to uncover insights in data that is beyond the reach of traditional analytics tools. The platform harnesses the huge parallelism of modern CPU/GPU hardware and is available both in the cloud or on-premise. HEAVY.AI was developed from research at Harvard and MIT Computer Science and Artificial Intelligence Laboratory. You can go beyond traditional BI and GIS and extract high-quality information from large datasets with no lag by leveraging modern GPU and CPU hardware. To get a complete picture of what, when and where, unify and explore large geospatial or time-series data sets. Combining interactive visual analytics, hardware accelerated SQL, advanced analytics & data sciences frameworks, you can find the opportunity and risk in your enterprise when it matters most.

The Apache Hadoop software library serves as a framework for the distributed processing of extensive data sets across computer clusters, utilizing straightforward programming models. It is built to scale from individual servers to thousands of machines, each providing local computation and storage capabilities. Instead of depending on hardware for high availability, the library is engineered to identify and manage failures within the application layer, ensuring that a highly available service can run on a cluster of machines that may be susceptible to disruptions. Numerous companies and organizations leverage Hadoop for both research initiatives and production environments. Users are invited to join the Hadoop PoweredBy wiki page to showcase their usage. The latest version, Apache Hadoop 3.3.4, introduces several notable improvements compared to the earlier major release, hadoop-3.2, enhancing its overall performance and functionality. This continuous evolution of Hadoop reflects the growing need for efficient data processing solutions in today's data-driven landscape.

Apache Spark™ serves as a comprehensive analytics platform designed for large-scale data processing. It delivers exceptional performance for both batch and streaming data by employing an advanced Directed Acyclic Graph (DAG) scheduler, a sophisticated query optimizer, and a robust execution engine. With over 80 high-level operators available, Spark simplifies the development of parallel applications. Additionally, it supports interactive use through various shells including Scala, Python, R, and SQL. Spark supports a rich ecosystem of libraries such as SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming, allowing for seamless integration within a single application. It is compatible with various environments, including Hadoop, Apache Mesos, Kubernetes, and standalone setups, as well as cloud deployments. Furthermore, Spark can connect to a multitude of data sources, enabling access to data stored in systems like HDFS, Alluxio, Apache Cassandra, Apache HBase, and Apache Hive, among many others. This versatility makes Spark an invaluable tool for organizations looking to harness the power of large-scale data analytics.

Direct is the fastest path from data to insight. Incorta empowers your business with a true self service data experience and breakthrough performance to make better decisions and achieve amazing results. Imagine if you could deliver data projects in days instead of weeks or months, instead of weeks and months with fragile ETL and expensive data warehouses. Our direct approach to analytics enables self-service on-premises or in the cloud with agility and performance. The world's most successful brands use Incorta to succeed where other analytics solutions fail. We offer connectors and pre-built solutions that can be used in your enterprise applications and technologies across multiple industries. Incorta's partners include Microsoft, eCapital and Wipro. They are responsible for delivering innovative solutions and customer success. Join our vibrant partner ecosystem.

Amazon EMR stands as the leading cloud-based big data solution for handling extensive datasets through popular open-source frameworks like Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi, and Presto. This platform enables you to conduct Petabyte-scale analyses at a cost that is less than half of traditional on-premises systems and delivers performance more than three times faster than typical Apache Spark operations. For short-duration tasks, you have the flexibility to quickly launch and terminate clusters, incurring charges only for the seconds the instances are active. In contrast, for extended workloads, you can establish highly available clusters that automatically adapt to fluctuating demand. Additionally, if you already utilize open-source technologies like Apache Spark and Apache Hive on-premises, you can seamlessly operate EMR clusters on AWS Outposts. Furthermore, you can leverage open-source machine learning libraries such as Apache Spark MLlib, TensorFlow, and Apache MXNet for data analysis. Integrating with Amazon SageMaker Studio allows for efficient large-scale model training, comprehensive analysis, and detailed reporting, enhancing your data processing capabilities even further. This robust infrastructure is ideal for organizations seeking to maximize efficiency while minimizing costs in their data operations.

Kraken caters to a wide range of users, from analysts to data scientists, by providing a user-friendly, no-code automated machine learning platform. It is designed to streamline and automate various data science processes, including data preparation, cleaning, algorithm selection, model training, and deployment. With a focus on making these tasks accessible, Kraken is particularly beneficial for analysts and engineers who may have some experience in data analysis. The platform’s intuitive, no-code interface and integrated SONAR© training empower users to evolve into citizen data scientists effortlessly. For data scientists, advanced functionalities enhance productivity and efficiency. Whether your routine involves using Excel or flat files for reporting or conducting ad-hoc analysis, Kraken simplifies the model-building process with features like drag-and-drop CSV uploads and an Amazon S3 connector. Additionally, the Data Connectors in Kraken enable seamless integration with various data warehouses, business intelligence tools, and cloud storage solutions, ensuring that users can work with their preferred data sources effortlessly. This versatility makes Kraken an indispensable tool for anyone looking to leverage machine learning without requiring extensive coding knowledge.

Scuba enables self-service analytics on a large scale, catering to various roles such as product managers, business unit leaders, chief experience officers, data scientists, business analysts, and IT personnel who will find it incredibly easy to access their data and extract valuable insights. By using Interana, you can delve deeper into understanding customer behavior, system performance, and application usage—essentially anything related to actions over time—transcending traditional dashboards and static reports. This unique analytics platform empowers you and your team to dynamically explore your data in real-time, providing clarity not only on what is happening in your business but also offering explanations for those occurrences. With Scuba, there's no delay in accessing your data; everything is readily available, allowing you to pose questions as fast as they come to mind. Designed with everyday business users in mind, Scuba eliminates the need for coding skills or SQL knowledge, making data exploration accessible to all. Consequently, businesses can make timely, informed decisions based on real-time insights rather than outdated information.

One platform with a diverse range of solutions, INDICA seamlessly integrates with all company applications and data sources. It effectively indexes real-time data, providing a comprehensive view of your entire data environment. Built on this robust platform, INDICA presents four distinct solutions. The INDICA Enterprise Search feature grants access to all corporate data sources via a single interface, indexing both structured and unstructured data while prioritizing results based on relevance. Meanwhile, INDICA eDiscovery can be tailored for individual cases or structured to facilitate swift fraud or compliance investigations. The INDICA Privacy Suite equips organizations with a comprehensive set of tools to ensure adherence to GDPR and CCPA regulations, maintaining ongoing compliance. Additionally, INDICA Data Lifecycle Management empowers you to oversee your corporate data, enabling efficient tracking, cleaning, or migration. Overall, INDICA’s data platform is designed with a wide array of features, ensuring you can effectively manage and control your data landscape while adapting to evolving business needs. This flexibility allows organizations to respond proactively to data challenges and opportunities.

Strategizing, innovating, and advancing. From identification of needs to implementation of solutions. Introducing the eDrain DATA CLOUD PLATFORM. This platform is designed specifically for the collection, monitoring, and generation of comprehensive reports on data. It functions within the realm of Big Data, utilizing a driver-centric approach that facilitates the integration of various types of data. The advanced driver engine allows for the simultaneous incorporation of numerous data streams and devices. Its features include the ability to customize dashboards, add different views, and create tailored widgets, along with configuring new devices, flows, and sensors. Users can also set up custom reports, monitor sensor statuses, and manage real-time data flows. Additionally, it enables the definition of flow logic, analysis rules, and warning thresholds, as well as configuration for events and actions. New devices can be created and new stations configured, allowing for the effective management and verification of alerts, ensuring a comprehensive data management experience. This platform empowers users to take full control of their data environment.

TIMi allows companies to use their corporate data to generate new ideas and make crucial business decisions more quickly and easily than ever before. The heart of TIMi’s Integrated Platform. TIMi's ultimate real time AUTO-ML engine. 3D VR segmentation, visualization. Unlimited self service business Intelligence. TIMi is a faster solution than any other to perform the 2 most critical analytical tasks: data cleaning, feature engineering, creation KPIs, and predictive modeling. TIMi is an ethical solution. There is no lock-in, just excellence. We guarantee you work in complete serenity, without unexpected costs. TIMi's unique software infrastructure allows for maximum flexibility during the exploration phase, and high reliability during the production phase. TIMi allows your analysts to test even the most crazy ideas.

Boost the pace of AI innovation through cloud-native data integration offered by IBM Cloud Pak for Data. With AI-driven data integration capabilities accessible from anywhere, the effectiveness of your AI and analytics is directly linked to the quality of the data supporting them. Utilizing a modern container-based architecture, IBM® DataStage® for IBM Cloud Pak® for Data ensures the delivery of superior data. This solution merges top-tier data integration with DataOps, governance, and analytics within a unified data and AI platform. By automating administrative tasks, it helps in lowering total cost of ownership (TCO). The platform's AI-based design accelerators, along with ready-to-use integrations with DataOps and data science services, significantly hasten AI advancements. Furthermore, its parallelism and multicloud integration capabilities enable the delivery of reliable data on a large scale across diverse hybrid or multicloud settings. Additionally, you can efficiently manage the entire data and analytics lifecycle on the IBM Cloud Pak for Data platform, which encompasses a variety of services such as data science, event messaging, data virtualization, and data warehousing, all bolstered by a parallel engine and automated load balancing features. This comprehensive approach ensures that your organization stays ahead in the rapidly evolving landscape of data and AI.

Delta Lake serves as an open-source storage layer that integrates ACID transactions into Apache Spark™ and big data operations. In typical data lakes, multiple pipelines operate simultaneously to read and write data, which often forces data engineers to engage in a complex and time-consuming effort to maintain data integrity because transactional capabilities are absent. By incorporating ACID transactions, Delta Lake enhances data lakes and ensures a high level of consistency with its serializability feature, the most robust isolation level available. For further insights, refer to Diving into Delta Lake: Unpacking the Transaction Log. In the realm of big data, even metadata can reach substantial sizes, and Delta Lake manages metadata with the same significance as the actual data, utilizing Spark's distributed processing strengths for efficient handling. Consequently, Delta Lake is capable of managing massive tables that can scale to petabytes, containing billions of partitions and files without difficulty. Additionally, Delta Lake offers data snapshots, which allow developers to retrieve and revert to previous data versions, facilitating audits, rollbacks, or the replication of experiments while ensuring data reliability and consistency across the board.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

Apache Storm is a distributed computation system that is both free and open source, designed for real-time data processing. It simplifies the reliable handling of endless data streams, similar to how Hadoop revolutionized batch processing. The platform is user-friendly, compatible with various programming languages, and offers an enjoyable experience for developers. With numerous applications including real-time analytics, online machine learning, continuous computation, distributed RPC, and ETL, Apache Storm proves its versatility. It's remarkably fast, with benchmarks showing it can process over a million tuples per second on a single node. Additionally, it is scalable and fault-tolerant, ensuring that data processing is both reliable and efficient. Setting up and managing Apache Storm is straightforward, and it seamlessly integrates with existing queueing and database technologies. Users can design Apache Storm topologies to consume and process data streams in complex manners, allowing for flexible repartitioning between different stages of computation. For further insights, be sure to explore the detailed tutorial available.

We are excited to introduce a groundbreaking big data platform designed for the music industry, which consolidates all relevant information into a single, reliable source to inform strategic decisions. Within the music business sector, numerous data sources exist, but they are often isolated and disjointed. Our innovative platform effectively identifies and integrates these sources, establishing a robust foundation of high-quality data applicable to everyday operations in the music industry. To operate effectively and securely while uncovering unique insights, record labels and agencies need an advanced data management and governance framework that ensures data is consistently accessible, pertinent, and practical. As data sources are integrated into Wavo’s Big Data Platform, machine learning techniques are utilized to categorize the data according to customized templates, facilitating easy access and deep dives into crucial information. This capability empowers every member of a music organization to harness and utilize data that is prepared and organized for immediate application and value creation. Ultimately, our platform serves as a catalyst for smarter decision-making and enhanced operational efficiency across the music business landscape.

SmartHub Analytics is a specialized platform for telecom big-data analytics that focuses on financial and subscriber-centric ROI-driven applications. It is specifically developed to foster data sharing and reuse, thereby enhancing business performance and providing analytics that are instantly actionable. By breaking down silos, SmartHub Analytics can evaluate, verify, and model extensive datasets from TEOCO’s array of solutions, which encompass areas like customer management, planning, optimization, service assurance, geo-location, service quality, and costs. Additionally, as an extra analytics layer integrated with existing OSS and BSS systems, SmartHub Analytics establishes an independent analytics environment that has demonstrated substantial returns on investment, allowing operators to save billions. Our approach frequently reveals substantial cost reductions for clients through the application of predictive machine learning techniques. Moreover, SmartHub Analytics consistently leads the industry by offering rapid data analysis capabilities, ensuring that businesses can adapt and respond to market changes with agility and precision.

bi(OS)® offers an unmatched speed to insight for developers of data applications in a cohesive manner. With bi(OS)®, the entire process of creating data applications can be completed in just a matter of hours to days. This comprehensive approach encompasses the integration of diverse data sources, the extraction of real-time insights, and the smooth deployment into production environments. By joining forces with enterprise data teams across various sectors, you can transform into the data superhero your organization needs. The combination of Open Source, Cloud, and SaaS has not fulfilled its potential for delivering genuine data-driven results. Enterprises have largely focused their investments on data movement and integration, a strategy that is ultimately unsustainable. A fresh perspective on data management is urgently required, one that considers the unique challenges of enterprises. bi(OS)® is designed by rethinking fundamental principles in enterprise data management, ranging from data ingestion to insight generation. It caters to the needs of API, AI, and BI developers in a cohesive manner, enabling data-driven outcomes within days. As engineers collaborate effectively, a harmonious relationship emerges among IT teams, tools, and processes, creating a lasting competitive advantage for the organization.