Best Data Management Software for Hive Data

Style Intelligence from InetSoft is a complete business intelligence platform that empowers companies with the ability to analyze, monitor, report and collaborate on business and operational data coming from different sources in real-time. Its top features include a data mashup Data Block architecture and professional atomic block modeling tool. There is also a database write-back option. Style Intelligence is robust and easy-to-use. It offers granular security, multitenancy support, multiple integrations, and is fully scalable.

Wyn is a seamless embedded business intelligence platform. Designed for self-service BI, Wyn's offers limitless visual data exploration, allowing the everyday user to become data-driven. Wyn Enterprise Features: • Embedded BI Seamlessly embed analytics within your own applications. Integrate dashboards into your business applications with API and iFrame capabilities. • End-user BI Reports Leverage Wyn's powerful and fast reporting engine to develop complex BI reports. • Interactive BI Dashboards Analyze data and deliver actionable information with interactive dashboards, multi-dimensional dynamic analysis, and intelligent drilling. • Easy-to-use Designers Drag-and-drop controls enable non-technical end-users to visualize, analyze, and distribute permitted data easily. • Self-service BI Eliminate your dependence on the IT departments and data analysts. Offer every end-user (from code-first to code-free) the ability to create custom ad hoc reports and interactive dashboards. • Built-in Multi-tenant Support Enhance your SaaS-based business applications with a BI platform that natively supports multi-tenancy. Manage your BI resources and data across all your customers from a single environment.

Bipp's cloud BI platform is powered by the bippLang Data modeling language. It was created for SQL and data analysts right from the beginning. It saves time for you and your team so that your business can make faster, better-informed decisions. BippLang data modeling language simplifies SQL queries by creating complex data models with custom columns, dynamic sub-querying, and reusable data. Git-based version control allows analysts to collaborate; all data models are automatically backed by the system. An always-free version allows you to access a powerful BI platform and professional support at no additional cost. In-database analytics makes it easy to access the data in a single system. This speeds up access and produces real-time results. Auto-SQL generator uses joins in the data model to determine which tables to join, and generate dynamic sub-queries based upon context. Data models that are single source of truth ensure that everyone in the organization can base business decisions on the same data.

The ever-on economy of today is creating data at an ever-increasing rate. It's important to be data-driven so that you can react quickly to new opportunities and stay ahead of your competitors. What if data provisioning and preparation could be simplified? What if you could share data insights across teams and perform database analysis more efficiently? Imagine if you could do this with a time saving of up to 40% Toad Intelligence Central, a server-based application, can be used in conjunction with Toad(r] Data Point. It transfers power back into your business at a cost-effective price. Secure, controlled access to SQL scripts, project artifacts and automation workflows can improve collaboration among Toad users. Advanced data connectivity allows you to easily abstract structured and unstructured data sources to create refreshable datasets that can be used by any Toad user.

Atlas is a flexible and extensible set core foundational governance services that enable enterprises to efficiently and effectively meet their compliance requirements within Hadoop. It also allows integration with the entire enterprise data ecosystem. Apache Atlas offers open metadata management and governance capabilities that allow organizations to create a catalog of their data assets, classify, govern and provide collaboration capabilities around these assets for data scientists, analysts, and the data governance group. Pre-defined types to manage various Hadoop and non Hadoop metadata. Ability to create new types to manage metadata. Types can inherit from other types, and can have simple attributes, complex attributes, and object references. Type instances, also known as entities, are able to capture metadata object details and their relationships. REST APIs allow for easier integration with types and instances.