There can be no doubt that the architecture for analytics has evolved
over its 25-30 year history. Many recent innovations have had significant
impacts on this architecture since the simple concept of a single
repository of data called a data warehouse. First, the data warehouse
appliance (DWA), along with the advent of the NoSQL revolution, selfservice analytics, and other trends, has had a dramatic impact on the
traditional architecture. Second, the emergence of data science, realtime operational analytics, and self-service demands has certainly had
a substantial effect on the analytical architecture.
Published By: FICO EMEA
Published Date: May 31, 2019
: FICO commissioned an independent research study by TM Forum to look at how global telecommunication providers are using (and plan to use) machine learning and advanced analytics to improve the customer experience in credit risk and beyond. This in-depth report includes key insights from a global survey as well as executive interviews with leading communication service providers such as Telstra, Vodafone, Sky, Globe Telecom, and BT on their vision for leveraging artificial intelligence to stop fraud, better engage customers across channels, improve risk management, and drive collection results.
Read this report to understand:
o What CSPs see as the biggest drivers for deploying advanced analytics over the next two years
o How and where BT, Globe Telecom, Vodafone UK, Sky and Telstra are using analytics, from marketing through origination
o The opportunities and pitfalls around financing devices as opposed to or in addition to subsidising them
o The scope for analytics to improve c
Published By: HPE Intel
Published Date: Mar 15, 2016
As more enterprises adopt technologies such as cloud, mobile, and analytics to help achieve strategic competitive advantage, CIOs and IT managers must support business-critical processes at a very high level across the enterprise. At the same time, IT organizations must manage complex hybrid IT infrastructures that include both cloud and on-premises technologies from multiple vendors and support providers. IDC believes that to tackle these challenges, IT organizations should look to support
providers for comprehensive offerings to help optimize IT operations and improve the efficiency of IT service delivery. In addition, IDC recommends that IT organizations looking to manage rapid change in today’s IT landscape consider support providers with a record of innovative support services and a focus on advanced technology in support delivery.
In the age of the customer, businesses realize the need to take their big data insights further than they have before, in order to win, serve, and retain their customers. Today’s modern company has more data than ever before and is now looking to derive insights from the data that will help propel it forward. As firms move data analytics to the cloud, there is a new set of challenges and barriers to overcome, but with the help of insights-platforms-as-a-service, companies will be able to innovate with data and drive business forward.
Published By: LogMeIn
Published Date: Mar 19, 2015
Remote support technology, including remote control, desktop sharing, and web collaboration, is one of the most popular platforms used across TSIA service disciplines. Today’s remote support solutions offer much more than just remote control for PCs, their functional footprint is expanding to include support for more devices and richer analytics for trend analysis and supervisor dashboards. Remote support solutions are typically well regarded by users, consistently delivering one of the highest average satisfaction scores in TSIA’s annual Global Technology Survey. Service executives should acquaint themselves with the new features and capabilities being introduced by leading remote support platforms and find ways to leverage the capabilities beyond technical support. Field services, education services, professional services, and managed services are all increasing adoption of these tools to boost productivity and avoid on-site visits. Download this white paper to learn more.
Watch our webinar, 4 Steps to Building a Customer Satisfaction Engine. SurveyMonkey's Director of Customer Success, Jeffrey Coleman, will show you how to:
- Ask questions that yield actionable data
- Scale follow-up actions and improvements
- Analyze survey data and get key metrics
- Close the loop by turning data into action
IT leaders working on customer service projects must display an incredible amount of diligence. An organization’s CRM system has become its lifeline to customers, but as customer needs evolve so has the requirements of CRM. According to Gartner, today’s CRM solution must include a laundry list of capabilities outside its traditional core functionality including: native mobile support of the vendor's customer service and support business applications; real-time analytics; industry-specific functionality and workflow; context mining of voice and text; scalable cloud-based systems; social media engagement; suggested next agent action; multimodal capabilities, such as chat within mobile self-service; and even co-browsing. Gartner surveyed the CRM field and evaluated each vendor including Pegasystems.
Download this Gartner Magic Quadrant analysis and gain a better understanding each vendors’ CRM Customer Engagement Center solutions.
Adobe sits at the nexus of content, media, and marketing.
Adobe provides an EMSS offering spanning marketing, advertising, analytics, and content management capabilities. Of the vendors included this study, Adobe maintains the highest degree of overall strategic focus on marketing and consumer engagement. Adobe is investing heavily in its platform’s core services to unify data, content, and shared functionality across products. Adobe stands out for its digital intelligence, content handling, and aggressive rollout of AI features. Reference clients praise Adobe for their application usability and account management.
Adobe article that condenses/highlights key findings from the Econsultancy Digital Marketing in the Financial Services and Insurance
Sector 2017 Study, an in-depth, 5000+ word report covering FSI executives’ opinions on:
– General trends in retail banking, investment banking, and insurance
– Internal structures their companies are using to execute digital transformation
– The biggest threats/disruptions in the industry
– The biggest priorities in 2017 (leaders are focusing on both customer retention and customer acquisition, mainstream is focusing just
on customer retention)
– Main sources of sales and leads (digital + mobile are steadily increasing sources)
– Digital marketing budgets & investment areas (leaders are investing more in digital marketing automation and analytics)
– Use of the cloud and AI to automate analysis and marketing
– The importance of multichannel personalization
– Innovation in the types/formats of products/services provided (leaders are focusing on i
Published By: Oracle CX
Published Date: Oct 20, 2017
Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been
top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar
database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as
quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data
from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure
1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP
database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks
can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data.
In-memory databases have helped address p
Published By: IBM APAC
Published Date: Nov 22, 2017
Using IBM Watson’s cognitive capabilities, companies can quickly differentiate their customer service quality by being more pro active and responsive to customer needs. Simply put, chatbots and virtual agents are the future of customer interactions. Building apps from scratch that incorporate natural language processing, speech to text recognition, visual recognition, analytics, and artificial intelligence requires broad expertise in these disciplines, large staffs, and a huge financial commitment. Making use of IBM Watson cognitive services brings these capabilities in-house quickly and without the capital investment that would be needed to develop the technologies within an organization.
Enterprises use data virtualization software such as TIBCO® Data Virtualization to reduce data bottlenecks so more insights can be delivered for better business outcomes. For developers, data virtualization allows applications to access and use data without needing to know its technical details, such as how it is formatted or where it is physically located. For developers, data virtualization helps rapidly create reusable data services that access and transform data and deliver data analytics with even heavylifting reads completed quickly, securely, and with high performance. These data services can then be coalesced into a common data layer that can support a wide range of analytic and applications use cases. Data engineers and analytics development teams are big data virtualization users, with Gartner predicting over 50% of these teams adopting the technology by 202
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