This independent whitepaper from the Kusnetzky Group Analyst describes the promise and challenges surrounding Big Data. It also validates the M7 solution from MapR, which simplifies big data management by consolidating disparate solutions into a single, enterprise-ready platform.
Forrester Research shares seven architectural qualities for evaluating Big Data production platforms.
In this webinar guest speaker Mike Gualtieri, Principal Analyst at Forrester, along with experts from MapR and Cisco, will present the following:
• The 7 architectural qualities for productionizing Hadoop successfully
• Architectural best practices for Big Data applications
• The benefits of planning for scale
• How Cisco IT is using best practices for their Big Data applications
• Mike Gualtieri, Principal Analyst at Forrester Research
• Jack Norris, Chief Marketing Officer at MapR Technologies
• Andrew Blaisdell, Product Marketing Manager at Cisco
• Sudharshan Seerapu, IT Engineer at Cisco
As the demand for Big Data analytics mushrooms, IT decision-makers must prepare for the widespread deployment of Hadoop. This Technical Insight Paper from the Evaluator Group outlines the key requirements that must be met to make Hadoop enterprise data center ready.
To extract value from an ever-growing onslaught of data, your organization needs next-generation data management, integration, storage and processing systems that allow you to collect, manage, store and analyze data quickly, efficiently and cost-effectively. That’s the case with Dell | Cloudera® Apache™ Hadoop® solutions for big data.
This business-oriented white paper summarizes the wide-ranging benefits of the Hadoop platform, highlights common data processing use cases and explores examples of specific use cases in vertical industries.
Download this ebook to learn the requirements for delivering trusted information to a modern data warehouse and the guiding principles for trusted information in next generation data warehouse environments.
Read the eBook to find out how the cloud model of paying only for the resources that you need—and only when you need them—supports experimentation and evaluation and is a great solution for short-term or occasional-use projects where investment in a dedicated cluster is cost prohibitive.
This paper focuses on the benefits of a queryable data store and big data technologies available to support data warehouse modernization. Read the paper to understand how data can be stored and optimized with Hadoop.
SAS Institute is gearing up to make a self-service data preparation play with its new Data Loader for Hadoop offering. Designed for profiling, cleansing, transforming and preparing data to load it into the open source data processing framework for analysis, Data Loader for Hadoop is a lynchpin in SAS's data management strategy for 2015.
This strategy centers on three key themes: 'big data' management and governance involving Hadoop, the streamlining of access to information, and the use of its federation and integration offerings to enable the right data to be available, at the right time.
Published By: Pentaho
Published Date: Jan 16, 2015
If you’re considering a big data project, this whitepaper provides an overview of current common use cases for big data, from entry-level to more complex. You’ll get an in-depth look at some of the most common, including data warehouse optimization, streamlined data refinery, monetizing your data, and getting a 360 degree view of your customer. For each, you’ll discover why companies are investing in them, what the projects look like, and key project considerations, including tools and platforms.
The end-to-end information integration capabilities of IBM® InfoSphere® Information Server are designed to help organizations understand, cleanse, monitor, transform and deliver data—as well as collaborate to bridge the gap between business and IT.
Read the IDC research report Shared Storage Offers Lower TCO than Direct-Attached Storage for Hadoop and NoSQL Deployments and learn how to:
Unify insights across various data sources and multiple cloud deployments
Reduce compute, capacity and operational costs
Increase security and prevent data loss
Plus, learn about the NetApp in-place analytics solution for your existing NAS data and how it can reduce infrastructure costs
Published By: Dell EMC
Published Date: Oct 08, 2015
This business-oriented white paper explains three options for starting your Hadoop journey. This paper also outlines the benefits of Hadoop and highlights some of the many use cases for this new approach to managing, storing and processing big data.
IBM® InfoSphere® Big Match for Hadoop helps you analyze massive volumes of structured and unstructured customer data to gain deeper customer insights. It can enable fast, efficient linking of data from multiple sources to provide complete and accurate customer information—without the risks of moving data from source to source. The solution supports platforms running Apache Hadoop such as IBM Open Platform, IBM BigInsights, Hortonworks and Cloudera.
Scalable data platforms such as Apache Hadoop offer unparalleled cost
benefits and analytical opportunities. IBM helps fully leverage the scale
and promise of Hadoop, enabling better results for critical projects and
key analytics initiatives. The end-to- end information capabilities of
IBM® Information Server let you better understand data and cleanse,
monitor, transform and deliver it. IBM also helps bridge the gap between
business and IT with improved collaboration. By using Information
Server “flexible integration” capabilities, the information that drives business
and strategic initiatives—from big data and point-of- impact analytics
to master data management and data warehousing—is trusted, consistent
and governed in real time.
Since its inception, Information Server has been a massively parallel
processing (MPP) platform able to support everything from small to very
large data volumes to meet your requirements, regardless of complexity.
Information Server can uniquely support th
Published By: Attunity
Published Date: Nov 15, 2018
With the opportunity to leverage new analytic systems for Big Data and Cloud, companies are looking for ways to deliver live SAP data to platforms such as Hadoop, Kafka, and the Cloud in real-time. However, making live production SAP data seamlessly available wherever needed across diverse platforms and hybrid environments often proves a challenge.
Download this paper to learn how Attunity Replicate’s simple, real-time data replication and ingest solution can empower your team to meet fast-changing business requirements in an agile fashion. Our universal SAP data availability solution for analytics supports decisions to improve operations, optimize customer service, and enable companies to compete more effectively.
Published By: Attunity
Published Date: Nov 15, 2018
IT departments today face serious data integration hurdles when adopting and managing a Hadoop-based data lake. Many lack the ETL and Hadoop coding skills required to replicate data across these large environments. In this whitepaper, learn how you can provide automated Data Lake pipelines that accelerate and streamline your data lake ingestion efforts, enabling IT to deliver more data, ready for agile analytics, to the business.