self service data

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Published By: Teradata     Published Date: May 02, 2017
Kylo overcomes common challenges of capturing and processing big data. It lets businesses easily configure and monitor data flows in and through the data lake so users have constant access to high-quality data. It also enhances data profiling while offering self-service and data wrangling capabilities.
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cost reduction, data efficiency, data security, data integration, financial services, data discovery, data accessibility, data comprehension
    
Teradata
Published By: SAS     Published Date: Apr 25, 2017
But if you can’t explain how you got the answer, or what it means, it’s no good. Most self-service BI solutions can only display what has already happened, through reports or dashboards. And most have a predefined path of analysis that gives users very little creative freedom to explore new lines of thought. To maintain competitive advantage, your BI solution should allow business users to quickly and easily investigate and interrogate the data to find out why something happened – to uncover the root cause behind the “what.”
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SAS
Published By: SAS     Published Date: Apr 25, 2017
Organizations in pursuit of data-driven goals are seeking to extend and expand business intelligence (BI) and analytics to more users and functions. Users want to tap new data sources, including Hadoop files. However, organizations are feeling pain because as the data becomes more challenging, data preparation processes are getting longer, more complex, and more inefficient. They also demand too much IT involvement. New technology solutions and practices are providing alternatives that increase self-service data preparation, address inefficiencies, and make it easier to work with Hadoop data lakes. This report will examine organizations’ challenges with data preparation and discuss technologies and best practices for making improvements.
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SAS
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
As a financial services provider, you have probably invested hundreds of thousands, if not millions of dollars, in building an analytic infrastructure. But, do your line-of-business analysts and managers have access to the data and insights they need, when they need them? Three ways Alteryx can help you improve customer experience, manage risk and increase operational efficiency Case studies on how your peer financial services companies are using self-service data analytics for a competitive edge
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Alteryx, Inc.
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
The traditional multiple-step, multi-tool legacy approach is a slow, time-consuming, and in most cases, a costly process that prevents organizations from making faster decisions with confidence. Data analysts today need an agile solution that empowers them to take charge of the entire analytics process. Download The Definitive Guide to Self-Service Data Analytics to: Understand why traditional analytic tools designed for data scientists are not ideal for data analysts like you Learn how self-service data analytics delivers the ease of use, speed, flexibility, and scalability you require See how Alteryx stacks up against traditional data prep and analytics tools
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Alteryx, Inc.
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
Data Analytics has become critical for many business decision makers. However, many of these managers and data analysts still rely on spreadsheets and other legacy-era tools that fall far short of current needs. As a result, they also rely heavily on a virtual army of data specialists and scientists, working under the auspices of a centralized analytics group, to prepare, blend, analyze, and even report on the critical data they need for decision making. Download this new paper to get the details behind self-service data analytics, and how it lets business analysts: Take charge of the entire analytical process, instead of relying on other departments Overcome limitations of legacy tools to save time and prevent errors Make more comprehensive and insightful business decisions at speed
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Alteryx, Inc.
Published By: Oracle     Published Date: Mar 29, 2017
We staan aan de vooravond van een technologische revolutie waarbij innovaties zoals Artificial Intelligence en Virtual Reality de customer experience zullen hervormen. Merken raken beter ingespeeld op digitale klanten die steeds meer de voorkeur geven aan self-service boven menselijke interactie. Aan de andere kant blijkt ook dat vele merken nog steeds worstelen met een van de meest fundamentele basisvereisten digitale CX: een optimale data-strategie.
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Oracle
Published By: Cisco     Published Date: Dec 21, 2016
Self-service analytics implies that users design and develop their own reports and do their own data  analysis with minimal support by IT. Most recently, due to the availability of tools, such as those from Qlik,  Spotfire, and Tableau, self-service analytics has become immensely popular. Besides powerful analytical  and visualization capabilities, they all support functionality for accessing and integrating data sources.  With respect to this aspect of data integration four phases can be identified in the relatively short history  of self-service analytics. This whitepaper describes these four phases in detail and shows how the tools  Cisco Data Preparation (CDP) and Cisco Information Server (CIS) for data virtualization can strengthen and  enrich the self-service data integration capabilities of tools for reporting and analytics.  
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Cisco
Published By: Veritas     Published Date: Dec 08, 2016
The latest version - Veritas NetBackup Platform 8.0 - delivers unified data protection for organizations of all sizes, with proven enterprise-class scale, high performance, extensive workload integration, and self-service. No matter where data resides, NetBackup is trusted today in small to the largest and most complex heterogeneous environments.
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cloud, cloud computing, data management
    
Veritas
Published By: Oracle     Published Date: Nov 14, 2016
This webinar shows how to get instant clarity with stunningly visual analysis and self-service discovery using Data Virtualization Cloud Service.
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marketing analytics, cloud, cloud computing, virtualization, cloud service, cloud, analytics, oracle
    
Oracle
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Today, businesses pour Big Data into data lakes to help them answer the big questions: Which product to take to market? How to reduce fraud? How to retain more customers? People need to get these answers faster than ever before to reduce “time to answer” from months to minutes. The data is coming in fast and the answers must come just as fast. The answer is self-service data preparation and analytics tools, but with that comes an expectation that the right data is going to be there. Only by using a data catalog can you find the right data quickly to get the expected insight and business value. Download this white paper to learn more!
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Waterline Data & Research Partners
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Business users want the power of analytics—but analytics can only be as good as the data. To perform data discovery and exploration, use analytics to define desired business outcomes, and derive insights to help attain those outcomes, users need good, relevant data. Executives, managers, and other professionals are reaching for self-service technologies so they can be less reliant on IT and move into advanced analytics formerly limited to data scientists and statisticians. However, the biggest challenge nontechnical users are encountering is the same one that has been a steep challenge for data scientists: slow, difficult, and tedious data preparation.
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Waterline Data & Research Partners
Published By: VMware     Published Date: Jul 01, 2016
Cloud computing adoption continues to expand as the overall benefits of cloud (cost efficiency, self-service, and IT standardization) are becoming more broadly recognized. While private cloud is the primary type of cloud infrastructure that is in use today, organizations are finding that cloud can no longer be a standalone IT sourcing and consumption model. Enterprises demand greater flexibility and scalability, leading them to invest in hybrid cloud models, which supply them with a seamless application, data, and management environment across all of their IT resources. IDC expects that the percentage of users who adopt private or public cloud models will diminish over the next several years, as enterprises increasingly choose to implement a hybrid cloud model.
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vmware data center, vcloud air, vsphere, hybrid cloud, public cloud, private cloud, disaster recovery, data center extension, data center replacement, date center modernization, virtual private cloud
    
VMware
Published By: IBM     Published Date: May 16, 2016
The data-driven organization is the new benchmark for success. Firms that harness data to dictate strategic and tactical decisions companywide make more informed business plans, better optimize operations, improve customer interactions, and provide competitive edge. To achieve these benefits, organizations increasingly see data refinement - transforming raw data from various sources into relevant and actionable information and delivering it through self - service access to any user who needs it - as the path toward success by helping break though immature processes and legacy systems. However, data refinement only functions as well as the strategies and approaches behind it. Organizations that do not understand the right way to embrace refinement will fail to catch up to competitors that have mastered the correct approach.
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ibm, forrester, data-driven organization, data, analytics, analytic architecture
    
IBM
Published By: SAS     Published Date: May 12, 2016
This paper examines the barriers to adoption from an IT and end-user perspective, and shows how self-service analytics in general – and SAS Visual Analytics in particular – can eliminate these barriers. Self-service analytics empowers users to truly exploit the wealth of data available to them, while ensuring that the IT organization maintains governance and control over that data.
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sas, business analytics, it organization
    
SAS
Published By: Pentaho     Published Date: Apr 28, 2016
Today, the need for self-service data discovery is making data governance a charged topic. As business-driven data discovery emerges as a fundamental need, the ability to ensure that data and analytics are trustworthy and protected becomes both more difficult and more imperative. This research explains how to manage the barriers and risks of self-service and enable agile data discovery across the organization by extending existing data governance framework concepts to the data-driven and discovery-oriented business. You’ll learn: - The implications of the "freedom vs. control" paradox - How to design for iterative, "frictionless" discovery - Critical checkpoints in data discovery process where governance should be in place
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pentaho, governed data, data and analytics, governance framework, freedom vs control, frictionless discovery
    
Pentaho
Published By: Oracle Service Cloud     Published Date: Mar 23, 2016
Consumer preference for customer service channels is changing across all ages and demographics. Adoption of digital customer service channels, with an emphasis on self-service channels such as web and mobile, is exploding as consumers expect relevant and seamless omnichannel customer service. However, firms’ technology and staffing plans are not keeping up with consumer demand for digital customer service. This report outlines communication channel customer use and major gaps in contact center technology and operations. It also provides data that will help application development and delivery (AD&D) pros align operations with customer expectations to garner their satisfaction and long-term loyalty.
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oracle, service cloud, forrester report, contact centers
    
Oracle Service Cloud
Published By: Rackspace     Published Date: Mar 08, 2016
This whitepaper examines how businesses can leverage the benefits of a Microsoft Private Cloud, and taking advantage of the following functions: •Enabling self-service. •Federating your Microsoft® Cloud Platform •Taking advantage of software-defined networking. •Messaging services. •Database as a Service (DBaaS) and its advantages.
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microsoft private cloud, microsoft cloud platform, rackspace, self-service, software-defined networking
    
Rackspace
Published By: Datawatch     Published Date: Dec 16, 2015
In this paper, the Top 10 Ways to Supercharge Analyst Productivity with Data Preparation, learn how a self-service data preparation solution saves analysts’ time by allowing them to manipulate, filter, enrich, blend and combine disparate data sets in a matter of minutes.
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data preparation, data wrangling, analyst productivity, data analysis, cleaning data, data blending
    
Datawatch
Published By: Looker     Published Date: Dec 03, 2015
The focus of modern business intelligence has been self-service; pushing data into the hands of end users more quickly with more accessible user interfaces so they can get answers fast and on their own. This has helped alleviate a major BI pain point: centralized, IT-dominated solutions have been too slow and too brittle to serve the business. What has been masked is a lack of innovation in data modeling. Data modeling is a huge, valuable component of BI that has been largely neglected. In this webinar, we discuss Looker’s novel approach to data modeling and how it powers a data exploration environment with unprecedented depth and agility. Topics covered include: • A new architecture beyond direct connect • Language-based, git-integrated data modeling • Abstractions that make SQL more powerful and more efficient
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Looker
Published By: IBM     Published Date: Nov 09, 2015
IBM believes the Data Warehouse market continues to expand and adapt to address new requirements for user self-service, increased agility, requirements for new data types, lower cost solutions, adoption of open source, driving better business insight, and faster time to value.
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ibm, data, magic quadrant, data management, analytics
    
IBM
Published By: SnapLogic     Published Date: Sep 03, 2015
Learn how SnapLogic and Amazon Web Services helped Earth Networks create a responsive, self-service cloud for data integration, preparation and analytics.
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data management, self-service clouding, data integration, data analytics, data storage, data encryption, data warehousing, database services, ssd storage
    
SnapLogic
Published By: F5 Networks Inc     Published Date: Jun 24, 2015
Enterprises are moving to a software-defined, private cloud data center model for agility, operational efficiency, and a self-service approach to deploying applications and associated services. They are utilizing a two-tier hybrid services architecture to get the benefits of specialized hardware for front door network services and scalable software for application, stack-specific services. Read this whitepaper to learn how to integrate the necessary services with the orchestration and automation systems of a software-defined data center.
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appplication services, cloud, software, load balancing, iot, agility, automation, operational efficiency
    
F5 Networks Inc
Published By: Waterline Data & Research Partners     Published Date: Jun 15, 2015
This analysis profiles products that can accelerate the shift toward business-user-oriented, visual, interactive data preparation.
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gartner, analysis, data visualization, business tools, best practices, interactivity, vendor functionality
    
Waterline Data & Research Partners
Published By: SAS     Published Date: Apr 16, 2015
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.
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SAS
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