When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for
the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics, and operations. Even so, traditional, latent data practices are possible, too.
Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and
discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. With the
right end-user tools, a data lake can enable the self-service data practices that both technical and business users need. These practices wring business value from big data, other new data sources, and burgeoning enterprise da
The future era of retailing has arrived, marked by dramatic signs of change. To stay competitive, retailers need to do three things quickly: using Social, Location and Mobile (SoLoMo) capabilities; enable shoppers’ desires for self-service retailing and assess current retail capabilities
IBM offers self-service BI capabilities that tell you what you need to know about the past, present and future—fast. Here are five reasons why you should choose IBM for self-service business intelligence.
Think of the self-service things you use in a day. Gas pumps. ATMs. Online apps for shopping. They’re convenient and easy to use. People choose what they want, when they want – without involving others in their minute-to-minute decisions. What if your organization could treat data discovery and analytics the same way?
SAS has combined two of its visual solutions to do just that. SAS Visual Analytics and SAS Visual Statistics share the same web-based interface to provide self-service data exploration and easy-to-use interactive predictive analytics in a collaborative environment. This white paper takes a look at this convergence and outlines how these products can be used together so that everyone, even nontechnical users, can investigate data on their own, create analytical models and uncover new insights that drive competitive differentiation. Your analytics journey just got a lot easier.
Approximately 79% of customers seeking customer service and support wish it were easier and more convenient to obtain.*
Read the new Customer Service Workbook to discover industry tips and best practices for bringing efficiency and profitability to order management while freeing up your CSRs to:
• Process orders quicker with fewer errors
• Carry out customer engagement strategies
• Manage order volumes at current staffing levels
• Increase customer loyalty
Virtualization is one of the most highly demanded of all IT projects this decade because it enables enterprises to reduce capex and opex costs and at the same time increase business efficiency and agility. However, implementing, supporting, and managing virtualization can often be difficult tasks, especially as deployments increase in scale and complexity and impact more areas of the datacenter. These more complex infrastructures often require highly skilled engineers with in-depth business knowledge and systems management capabilities. Projects such as infrastructure optimization and automation initiatives for self-service provisioning are key because they enable enterprises to streamline business processes and utilize cloud strategies and mobility solutions. IDC shows how partnering with experts who can implement, optimize, support, and manage virtualized environments may be the right course of action. By utilizing partners, enterprises will be able to avoid some of the potential pit
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.
In this eBook you’ll read case studies about top enterprises that have safely enabled BYOD and self-service capabilities with an EMM platform, providing IT with an opportunity to enable process transformations and drive new revenue streams.
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.”
Business intelligence has come a long way ? from assistance with report generation to self-service platforms for discovery and analytical insight. As technological capabilities and business aptitude with information continue to advance, the next generation of BI will be even more capable and valuable to the enterprise. To discuss today’s success factors and tomorrow’s opportunities, IIA spoke with Andy Bitterer, Senior Director of Business Intelligence Product Management at SAS, and Tapan Patel, Principal Product Marketing Manager at SAS.
IT organizations are largely siloed between the desktop and mobile management worlds. IT has addressed management of mobile devices with modern enterprise mobility management (EMM) solutions. However, Windows desktops have been managed separately using older PC lifecycle management (PCLM) technologies, which have fallen short of basic IT and end user expectations of today’s evolved, mobile-cloud workforce.
The VMware AirWatch® Unified Endpoint Management (UEM) solution is a single, platform-independent approach for managing every device and every operating system across any organizational use case. The solution combines traditional client management requirements with modern EMM efficiencies enabling IT to deliver OS policies, patches, and apps over-the-air. Cloud-first management with instant push technologies and self-service capabilities ensure lower cost management, better security, and peak user experience regardless of the device being used to access the corporate environment.
Authored by two luminary Business Intelligence (BI) industry analysts. This 9 page report exposes best practices on Self-Service BI. The findings come from a Q3'12 survey on BI, which captured the experiences of 327 organizations.
Customer relationship management (CRM) deployments are most effective when they legitimately support all three words that make up the acronym itself. Customers of the modern business-to-business (B2B) enterprise benefit when they purchase goods and services from companies who are focused on the buyer’s experience. Internal relationships within the selling organization are more effectively maintained when all customer-facing stakeholders have access to the rich data contained in a well-maintained CRM. And the management of the enterprise providing solutions can run their business like a finely-tuned machine when the maximum levels of visibility into customers and accounts are clear and accurate. This Research Brief combines research from a number of Aberdeen Sales Effectiveness research data sets, to create a holistic view of the most effectively deployed CRM systems.
The move towards self-service is clearly about mitigating costs. But self-service models can also deliver significant benefits to users when they combine the best of online convenience with the insight and personal touch of an experienced sales or service rep.
Published By: Clickatell
Published Date: May 20, 2008
In meeting the challenges of an increasingly competitive banking landscape, Standard Bank seeks to differentiate itself by providing the highest levels of service to its customer base. An integral part of achieving this goal has been its partnership with Clickatell to deliver personalized and relevant messaging to bank customers via their mobile phones. Read this case study to learn more.
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.
The importance of healthcare providers to assure their patients the utmost security, confidentiality and integrity of their sensitive information cannot be understated. This means being HIPAA compliant within every aspect of their practice, with a particular emphasis on the components of their healthcare IT infrastructure
This white paper described elements and best practices of a HIPAA compliant data center. This comprehensive guide spans the administrative, physical, and technical safeguards of the HIPAA Security rule from the physical security and environmental controls necessary of the facility itself, to the requirements needed between a Covered Entity (CE) and the data center provider when outsourcing.
Detailing both the benefits and risks of a third-party partnership, this white paper provides answers to key questions such as what exactly makes a data center HIPAA compliant, what to look for when choosing a service provider to work with, and why a Business Associate Agreement (BAA) is important for establishing accountability with these partners.
La mobilité reste une opportunité stratégique importante
pour les entreprises de toutes sortes, car elle peut contribuer
à augmenter leur compétitivité en rendant les employés plus
productifs ou en s'engageant auprès des clients de manière
plus innovante. Pour atteindre ce potentiel, la mobilité des
entreprises doit proposer aux utilisateurs une expérience simple
sur plusieurs terminaux et offrir un espace de travail sécurisé
pour les applications essentielles. Pour servir cette base d'employés mobiles et de clients, les entreprises doivent activer leurs fonctionnalités BYOD et self-service avec une plateforme établie qui s'adapte pour prendre en charge de nouveaux processus.
La plateforme de gestion de la mobilité d'entreprise (EMM)
offre à l'informatique la possibilité d'activer les transformations
de processus métier, de favoriser de nouveaux revenus et de créer de nouvelles façons mémorables de se connecter aux clients.
This white paper takes a look at the current challenges that many
organizations face in addressing this growing need. It examines the
different types of users and stakeholders who need or want more
self-service, and lays out four factors that are critical to realizing the
full potential of self-service analytics.
The car industry’s fortunes play an important part in the stability of the broader economy. Consumers shopping for and financing a new or used vehicle have more choices than ever before. Empowered by digital delivery channels such as self-service and mobile, individuals are now able to rapidly choose and the vehicle and loan that best fits their needs.
Data is the lifeblood of business. And in the era of digital business,
the organizations that utilize data most effectively are also the most
successful. Whether structured, unstructured or semi-structured,
rapidly increasing data quantities must be brought into organizations,
stored and put to work to enable business strategies. Data integration
tools play a critical role in extracting data from a variety of sources and
making it available for enterprise applications, business intelligence
(BI), machine learning (ML) and other purposes. Many organization
seek to enhance the value of data for line-of-business managers by
enabling self-service access. This is increasingly important as large
volumes of unstructured data from Internet-of-Things (IOT) devices
are presenting organizations with opportunities for game-changing
insights from big data analytics. A new survey of 369 IT professionals,
from managers to directors and VPs of IT, by BizTechInsights on
behalf of IBM reveals the challe
Don’t just generate insights. Generate inspiration. Automating data enables easier, faster, better self-service insights better insights, giving your company power to innovate and be creative. Discover the endless possibilities in our webinar.