Showing posts with label Apache Hadoop. Show all posts
Showing posts with label Apache Hadoop. Show all posts

Sunday, June 18, 2017

IBM and Hortonworks joined hands to Help Businesses Accelerate Data-Driven Decision Making

Are you looking for information on Database and Cloud related services from IT firms? If so read this article to know little information on Data-Driven Decision Making initiative between two reputed IT companies, IBM and Hortonworks.

Business organization around the world has their clients' various data that they have to use for their regular business operation which also needs to be secured and retrieved always. The data is not only confidential but challenges as well to keep them secure for a long time due to various reasons like server issue, malware, phishing, hacking, cyber crime issue and on. 


Image courtesy: IBMBigDataHub.com

So, the larger IT or third party IT companies accepts these data maintenance work from such business organization to take care of them on behalf, so, the same responsible of securing and maintaining the data's of their client increases, duration increases thus their data increases as well. 

It is not impossible to serve them but they have to face the challenges as well for a long after number of data and clients increasing further. So, Data using organization and its maintenance IT industry has to go together for a long.

IBM (NYSE: IBM) and Hortonworks (NASDAQ: HDP) recently announced an expansion to their relationship focused on extending data science and machine learning to more developers and across the Apache Hadoop ecosystem. Would you like to know how they can work together for data-driven business? Read it then. 

The companies are combining Hortonworks Data Platform (HDP®) with IBM Data Science Experience and IBM Big SQL into new integrated solutions designed to help everyone from data scientists to business leaders better analyze and manage their mounting data volumes and accelerate data-driven decision-making. 

IBM and Hortonworks partnership overview:

Companies combine IBM Data Science Experience and Machine Learning with Hortonworks Data Platform;
New fast and easy on ramp for developers to access data science and cognitive tools and create intelligent apps;
Companies to propel Apache open source projects with new code

The news builds on the long-standing relationship between the companies and includes the following:

How IBM and Hortonworks partnership will function

Hortonworks will resell the IBM Data Science Experience with HDP, a leading Hadoop distribution, and adopt it as its strategic data science platform, giving developers a fast on-ramp to data science capabilities including machine learning, advanced analytics and statistics. 

Hope you got it little bit here. Read it for more detail. Hortonworks and IBM will create new solution bundles that integrate HDP with IBM Big SQL, IBM’s SQL engine for Hadoop, giving Hortonworks’ legions of clients and users a familiar method of managing their data.

IBM is adopting HDP for its Hadoop distribution and will fully integrate it with Data Science Experience and Machine Learning. So, they would continuously work together on this. 

As a result, this solution will combine for users the rich data security, governance and operations functionality provided by HDP, and the advanced analytics and management of the Data Science Experience. IBM will migrate existing IBM BigInsights users to HDP.

IBM Data Science Experience provides a set of critical tools and a collaborative environment through which analysts and developers can create new analytic models quickly and easily. Analytic works better in every data for the stats combination. 

For example, IBM Machine Learning, found in the Data Science Experience, can speed the time it takes to build and deploy analytic models for application development by two-times, according to IBM testing.

In addition to the companies’ numerous product collaborations, IBM and Hortonworks are also founding members of the Open Data Platform Initiative (ODPi). 

Hope you know little bit about it, however if not, it was launched in February 2015, ODPi is comprised of industry leaders working collaboratively to define and promote a set of standard open source technologies and increase compatibility among big data platforms.

The expanded partnership also builds on an existing partnership and joint solutions including HortonWorks Data Platform (HDP) for IBM's Power Systems and Spectrum Scale Storage. Customers can benefit from fast access to data and a cost-effective platform for running their big data and cognitive workloads.

Hortonworks recently announced Hortonworks DataFlow (HDFTM) for IBM Power Systems. HDF, the industry’s only data ingest, stream processing and streaming analytics platform built entirely on open source software, is designed to enable customers to collect, curate, analyze and act on all data in real-time, across the data center and cloud. 

The database business to booming around. Combined with IBM Power Systems, customers can gain access to industry-leading performance and efficiency for streaming analytics. HDF is complementary to HDP and is designed to accelerate the flow of data in motion into HDP to support full fidelity analytics.

Partnering On Apache
As part of their wide-ranging partnership, the companies will also team to advance the development of Unified Governance (IBM BigIntegrate, IBM BigQuality and IBM Information Governance Catalog) on the Apache Atlas open platform. 

Atlas provides a scalable governance platform for Enterprise Hadoop which is designed to help developers model new business processes and data assets quickly and easily. Through their work, both companies plan to help advance Atlas from its current Incubator status to Apache Top Level Project status, where projects are typically released for open development and deployment.

In addition to Atlas, the companies will also partner on the advancement of Apache Spark, the open source framework for processing and analyzing large data sets across clustered environments. 

The companies will also collaborate to advance the Apache Hadoop framework itself, working to unify access to multi-vendor, heterogeneous data environments across data warehouses and databases – ultimately  aiming to simplify the environment for better value from all data.

“The combination of IBM’s data science and Hortonworks’ open and connected data platforms will benefit not only our respective clients, but also the Apache open source community because of our combined investment and collaboration,” said Rob Bearden, CEO, Hortonworks. “We’re excited about the inevitable acceleration in technical innovations that this relationship is being designed to foster, the result being smarter and more agile businesses.”
           
“This partnership will provide an integrated and open data science and machine learning platform that lets teams easily collaborate and operationalize data science,” said Rob Thomas, General Manager, IBM Analytics. “Incorporating advanced machine learning and deep learning capabilities, the combination of Hortonworks Data Platform with IBM's Data Science Experience and the IBM Machine Learning platform can help clients achieve improved analytic results faster and at scale.”

Pros and cons of Data-Driven business
Though there are many pros on the database driven business, there could be few cons too like a hacking etc.

Data-drive is a risky business and smooth operation required when needed which needs to be maintained for a long

The competitor of Data driven business increases

IBM, a Leader in Gartner Data Science Magic Quadrant. IBM was recently named a Leader in the February 2017 Gartner Magic Quadrant for Data Science Platforms. 

Hortonworks, is an industry-leading innovator that creates, distributes and supports enterprise-ready open data platforms and modern data applications that deliver actionable intelligence from all data: data-in-motion and data-at-rest. 

Note: This is a Press Release, thus, most of the points and paragraphs would be the same as PR and not to be considered as copied content overall.