Summary: Big Data Suite
The big news is out – Pivotal Big Data Suite is now available from IBM. Pivotal Big Data Suite provides data warehouse solutions to small, medium and large businesses with a full range of analytical processing power and software support for Hadoop, Spark, R, ML, SML and Pyels.
IBM’s award-winning Cognitive Computing Power Software (CCP) and IBM’s DeepCQ Solutions have been integrated into Pivotal Big Data Suite to deliver unprecedented results from the leading enterprise applications run on the IBM Cloud.
Features: Spring XD
With Pivotal Big Data Suite, customers can: Design, Create, Measure and Explore…Embrace the Intelligence of the Cloud – “The cloud is all around us”. Reduce Operational Costs with on Demand Instances – “demand instances” are a highly efficient use of resources that can be instantly deployed without any additional infrastructure expense.
With Pivotal big data suite, enterprises can: Build enterprise intelligence tools using the most up-to-date tools and analytic language tools. Apply big data analytics to help solve business problems by collecting, analyzing and managing enterprise data. Streamline data warehousing procedures with fully generic, purpose built tools for easy deployment across an array of devices and platforms. Manage and optimize data through tools for data mining, multi-tier data warehousing and advanced analytics.
When compared to other cloud-based big data suite products, Pivotal Big Data Suite has several distinct advantages over the rest. Pivotal Big Data Suite is built on the IBM Cloud using the IBM Information Server (BIOS) platform, which enables customers to easily deploy and scale the software.
Users can also rapidly upgrade their software, adding new features as they become available. As a subscription-based business solution, users have access to a customized, tailored cloud environment. Through a flexible subscription model, Pivotal Big Data Suite delivers the following benefits:
Scalability is one of the biggest benefits offered by Pivotal Big Data Suite. Through a number of add-in or associate applications, users can rapidly and easily increase or decrease the size of their data sets.
For instance, they can create a smaller footprint through the use of container apps, and quickly make the necessary adjustments on their own. The flexibility offered by Pivotal Big Data Suite helps customers to rapidly grow their data sets in ways they might not have been able to do on their own. It can also help customers make informed decisions about the size of their cloud environment.
One of the largest selling points of Pivotal Big Data Suite is that it offers high quality analytics on large and complex data sets. Big Data analytics is the foundation for advanced Hadoop collections. Hadoop Distributed Resource Planning (DPR) is an open source framework that promises to dramatically reduce the total cost of running a single Hadoop cluster.
Through Pivotal Big Data Suite, users will be able to gain insight into their data sets and the underlying Hadoop framework. This will in turn give them greater insight into what their customers are asking for and the capabilities of their Hadoop stack.
A big part of running an online retail business is managing inventory and tracking sales. But managing orders, returns, and funding is just the beginning. Inventory tracking is just the first part of an effective ERP system, and is only the beginning. Because of this, Pivotal Big Data Suite offers a full range of solutions for managing workflow automation, manufacturing control, finance, and accounting.
As an end-to-end ERP solution, Big Data Suite makes managing an online retail operation faster, easier, and more accurate than ever before.
Designed to help Apache Spark, Hadoop, and other distributed applications run efficiently across large numbers of machines, developers behind Pivotal Big Data Suite are looking to extend the functionality of existing software and to provide developers with more flexibility and control.
In response to this, the suite has been designed with two modular – Big Data Analytics and Workflow Automation.
Big Data Analytics
Through the Big Data Analytics module, application owners will be able to import their ERP data from their servers and convert it into predictive dashboards, data visualizations, and third party integration services such as Yafoo and Placewe.
Big Data Workflow Automation.
The Workflow Automation module will enable developers to run workflows on their own machines without needing any programming knowledge, and will also improve scalability and decrease server load.
Developers in the Hadoop community are excited by the prospects of this new Big Data platform. With its several spring XD features, developers are able to take advantage of several new opportunities.
Ambari is one of the largest players in the Hadoop ecosystem, providing functionality for both ingesting large amounts of data and storing it in HD clusters. By taking full advantage of Ambari’s capabilities, companies can take their distributed data collection efforts to the next level with more predictability and increased agility.