Published By: Cloudian
Published Date: Jun 08, 2015
For companies looking to build their own cloud storage infrastructure, including enterprise IT organizations and cloud service providers or cloud hosting providers, the decision to use cloud and cloud storage for the delivery of IT services is best made by starting with the knowledge and experience gained from previous work. This white paper gathers into one place the essentials of a scale-out storage reference architecture coupled with a real world example from the Cloudian support organization that is using the Cloudian HyperStore appliances and the Hortwonworks Hadoop Data Platform to analyze Big Data logs and troubleshoot customer issues.
This paper discusses the role of the QlikView Business Discovery platform as the foremost user-friendly analytics platform accompanying a Big Data solution. It is written for IT professionals and business leaders who are trying to understand how to gain the most leverage from a Big Data implementation by providing an analytics layer that can both access the data and make it relevant and accessible to the business users in an organization.
Data centers face financial pressure as server-side compute cycles grow while space, power, and funds continue to be limited. Increased demand for compute capacity comes from growth in mobile devices, big data and analytics, cloud computing, media consumption, hosted desktops, and more. Data center managers find themselves maxed out on storage, power, cooling, space, storage, and compute capacity. Even with virtualization, there is a capacity limit to existing resources. Building more facilities is an option, but the emerging technology of ultra-dense computing offers a more compelling financial alternative for many common workloads.
Customer demands have led to recent changes in the data warehouse market. As a result, companies and departments of all types and sizes can leverage advanced data warehouse solutions to facilitate effective use of innovative business analytics and support of various mission-critical business intelligence initiatives.
IBM DB2 with BLU Acceleration helps tackle the challenges presented by big data. It delivers analytics at the speed of thought, always-available transactions, future-proof versatility, disaster recovery and streamlined ease-of-use to unlock the value of data.
If you function like most IT organizations, you've spent the past few years relying on mobile device management (MDM), enterprise mobility management (EMM) and client management tools to get the most out of your enterprise endpoints while limiting the onset of threats you may encounter.
In peeling back the onion, you'll find little difference between these conventional tools and strategies in comparison to those that Chief Information Officers (CIOs) and Chief Information Security Officers (CISOs) have employed since the dawn of the modern computing era. Their use has simply become more:
Time consuming, with IT trudging through mountains of endpoint data;
Inefficient, with limited resources and limitless issues to sort through for opportunities and threats; and
Costly, with point solution investments required to address gaps in OS support across available tools.
Download this whitepaper to learn how to take advantage of the insights afforded by big data and analytics thereby usher i
If you are working with massive amounts of data, one challenge is how to display results of data exploration and analysis in a way that is not overwhelming. You may need a new way to look at the data – one that collapses and condenses the results in an intuitive fashion but still displays graphs and charts that decision makers are accustomed to seeing. And, in today’s on-the-go society, you may also need to make the results available quickly via mobile devices, and provide users with the ability to easily explore data on their own in real time.
SAS® Visual Analytics is a data visualization and business intelligence solution that uses intelligent autocharting to help business analysts and nontechnical users visualize data. It creates the best possible visual based on the data that is selected. The visualizations make it easy to see patterns and trends and identify opportunities for further analysis.
The heart and soul of SAS Visual Analytics is the SAS® LASR™ Analytic Server, which ca
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
Big data and personal data are converging to shape the internet’s most surprising consumer products. they’ll predict your needs and store your memories—if you let them. Download this report to learn more.
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.
This paper explores the results of a survey, fielded in April 2013, of 304 data managers and professionals, conducted by Unisphere Research, a division of Information Today Inc. It revealed a range of practical approaches that organizations of all types and sizes are adopting to manage and capitalize on the big data flowing through their enterprises.
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
Over the course of several months in 2011, IDC conducted a research study to identify the opportunities and challenges to adoption of a new technology that changes the way in which traditional business solutions are implemented and used. The results of the study are presented in this white paper.
Forrester conducted in-depth surveys with 330 global BI decision-makers and found strong correlations between overall company success and adoption of innovative BI, analytics, and big data tools. In this paper, you will learn what separates the leading companies from the rest when it comes to exploiting innovative technologies in BI and analytics, and what steps you can take to either stay a leader or join their ranks.
This white paper, produced in collaboration with SAP, provides insight into executive perception of real-time business operations in North America. It is a companion paper to Real-time Business: Playing to win in the new global marketplace, published in May 2011, and to a series of papers on real-time business in Europe, Asia-Pacific and Latin America.
Leading companies and technology providers are rethinking the fundamental model of analytics, and the contours of a new paradigm are emerging. The new generation of analytics goes beyond Big Data (information that is too large and complex to manipulate without robust software), and the traditional narrow approach of analytics which was restricted to analysing customer and financial data collected from their interactions on social media. Today companies are embracing the social revolution, using real-time technologies to unlock deep insights about customers and others and enable better-informed decisions and richer collaboration in real-time.
Published By: Pentaho
Published Date: Feb 26, 2015
This TDWI Best Practices report explains the benefits that Hadoop and Hadoop-based products can bring to organizations today, both for big data analytics and as complements to existing BI and data warehousing technologies.
Published By: Pentaho
Published Date: Nov 04, 2015
Amid unprecedented data growth, how are businesses optimizing their data environments to ensure data governance while creating analytic value? How do they ensure the delivery of trusted and governed data as they integrate data from a variety of sources?
If providing appropriately governed data across all your data sources is a concern, or if the delivery of consistent, accurate, and trusted analytic insights with the best blended data is important to you, then don’t miss “Delivering Governed Data For Analytics At Scale,” an August 2015 commissioned study conducted by Forrester Consulting on behalf of Pentaho.
Published By: Pentaho
Published Date: Nov 04, 2015
This report explains the benefits that Hadoop and Hadoop-based products can bring to organizations today, both for big data analytics and as complements to existing BI and data warehousing technologies based on TDWI research plus survey responses from 325 data management professionals across 13 industries. It also covers Hadoop best practices and provides an overview of tools and platforms that integrate with Hadoop.