Published By: Cisco EMEA
Published Date: Nov 08, 2018
Digital transformation (DX) — a technology-driven business strategy — enables firms to gain or expand their competitive differentiation by embracing data-driven decision-making processes, whether for increasing operational efficiencies, developing new products and services, increasing customer satisfaction and retention, or getting a better intelligence on the market.
Big Data and analytics (BDA) applications form the foundation for enterprisewide digital transformation initiatives.
To find out more download this whitepaper today.
Published By: Aberdeen
Published Date: Jun 17, 2011
Download this paper to learn the top strategies leading executives are using to take full advantage of the insight they receive from their business intelligence (BI) systems - and turn that insight into a competitive weapon.
It’s no secret financial services organizations own and operate legacy solutions. Some of these core processes are front and center, meeting customer needs; others are in the middle, supporting account handling operations; and still many more are in the back-office, handling data and managing analytics. The challenge for financial leaders is to ensure these traditional systems don’t prevent the delivery of great digital experiences now and into the future.
To find out more download this eBook today.
Published By: Workday UK
Published Date: Sep 18, 2018
People analytics is increasingly on the agenda for organisations. With the rise of workplace technology allowing leaders to track employees’ performance, productivity and wellbeing, we partnered with the CIPD to survey over 3,000 business professionals to understand how people analytics is being used.
And the results are in. 65% of respondents who work in an organisation with a strong people analytics culture, say their business performance is strong compared to competitors.
As well as outlining the key opportunities leaders can capitalise on, this report covers:
- How different professions are using people data
- The various types of people data that are being used
- How people analytics adds value to organisations
- What the future holds for people data
In today’s world, advanced vision technologies is shaping the next era of Internet of Things. However, gathering streaming video data is insufficient. It needs to be timely and accessible in near-real time, analyzed, indexed, classified and searchable to inform strategy—while remaining cost-effective.
Smart cities and manufacturing are prime examples where complexities and opportunities have been enabled by vision, IoT and AI solutions through automatic meter reading (AMR), image classification and segmentation, automated optical inspection (AOI), defect classification, traffic management solution—just to name a few.
Together, ADLINK, Touch Cloud, and Intel provide a turnkey AI engine to assist in data analytics, detection, classification, and prediction for a wide range of use cases across a broad spectrum of sectors.
Learn more about how the Touch Cloud AI brings cost savings, operational efficiency and a more reliable, actionable intelligence at the edge with transformative insi
From protecting customer experience to preserving lines of revenue, IT operations teams face increasingly complex responsibilities and are responsible for preventing outages that could harm the organization. As a Splunk customer, your machine data platform empowers you to utilize machine learning to reduce MTTR. Discover how six companies utilize machine learning and AI to predict outages, protect business revenue and deliver exceptional customer experiences.
Download the e-book to learn how:
Micron Technology reduced number of IT incidents by more than 50%
Econocom provides better customer service by centralizing once-siloed analytics, improving SLA performance and significantly reducing the number of events
TransUnion combines machine data from multiple applications to create an end-to-end transaction flow
Predictive IT is a powerful new approach that uses machine learning and artificial intelligence (AI) to predict incidents before they impact customers and end users. By using AI and predictive analytics, IT organizations are able to deliver seamless customer experiences that meet changing customer behavior and business demands. Discover the critical steps required to build your IT strategy, and learn how to harness predictive analytics to reduce operational inefficiencies and improve digital experiences.
Download this executive brief from CIO to learn:
5 steps to an effective predictive IT strategy
Where AI can help, and where it can’t
How to drive revenue and exceptional customer experiences with predictive analytics
Published By: Workday
Published Date: Sep 19, 2018
Hoarding data isn’t doing much to help your financial services firm if you can’t easily combine data from multiple sources and quickly run analytics. But there is a way to turn those heaps of data into actionable insights to get clearer answers to your biggest questions and better drive your firm’s strategy. Read the blog to learn how to improve your back end to go from data hoarding to decision-making.
Adobe offers powerful personalization tools that help you give your customers custom experiences every time they interact with you. With Adobe, you can take control of your data, use AI to achieve scale, and see incredible results.
Adobe Target helps marketers deliver relevant, personalized experiences to highly targeted audiences based on behavioral analytics and audience data. Powered by AI and machine learning, users can deliver individualized customer experiences at massive scale.
Published By: StreamSets
Published Date: Dec 05, 2018
Enterprise analytics is quickly evolving into a democratized capability where anyone can access and act on all available information, often in real-time employing advanced techniques. But the complex, dynamic and urgent nature of modern data analytics demands a new approach to data integration.
This paper proposes that DataOps, the application of DevOps practices to data analytics, is the best way to overcome these challenges to create an iterative build-operate process for data movement.
Read this white paper to:
Understand how modern data analytics create data integration challenges due to architectural complexity, operational blindness and data drift.
Learn how DevOps pillars of automation and monitoring can create higher developer productivity, operational efficiency and business confidence in data.
See specific examples of DataOps functionality being applied to data integration across modern architectures.
Deep learning opens up new worlds of possibility in artificial intelligence, enabled by advances in computational capacity, the explosion in data, and the advent of deep neural networks. But data is evolving quickly and legacy storage systems are not keeping up. Read this MIT Technology Review custom paper to learn how advanced AI applications require a modern all-flash storage infrastructure that is built specifically to work with high-powered analytics, helping to accelerate business outcomes for data driven organizations.
Data is the new currency. Is your organization capitalizing on the full potential of data analytics? In this big data primer, you will learn about the 3 key challenges facing organizations today: managing overwhelming amounts of data, leveraging new complex tools/technologies, and developing the necessary skills and infrastructure. And since storage is where your organization's data lives, it’s a pivotal part of the infrastructure jigsaw puzzle. Thus with a “tuned for everything” storage solution that is purpose-built for modern analytics, you can confidently harness the power of your data to drive your enterprise forward.
Published By: Infosys
Published Date: Dec 03, 2018
Data is a truly inexhaustible resource for an organization. It creates endless possibilities to make data do more. As a technology partner of hundreds of organizations around the world, Infosys helps clients navigate the journey from their current state to the next.
Facilitating clients’ transition into data-native enterprises is a crucial part. To understand how companies are using data analytics today and their expectations in a world of endless possibilities with data, we recently commissioned an independent survey of 1,062 senior executives from organizations with annual revenues exceeding US$ 1 billion, in the United States, Europe, Australia, and New Zealand. The respondents were from business and technology roles, who were decision makers, program managers and external consultants; represented 12 industries, grouped into seven industry clusters, such as, consumer goods, retail and logistics, energy and utilities, financial services and insurance, healthcare and life sciences, h
Download this free e-guide to gain an understanding of predictive analytics concepts, how to align your data sources to unlock the value of the data in your organization, analyze the correlations, and reap the benefits of analytics in optimizing sales performance.
The use of data analytics as a driver for increased efficiencies and better customer service is proving valuable across industries. In the QSR space, data analytics is being adopted as a way to help QSRs stay competitive and grab a larger share of the market, as customers increasingly include speed and convenience as important factors in choosing where to eat.
Published By: Mindfire
Published Date: May 07, 2010
In this report, results from well over 650 real-life cross-media marketing campaigns across 27 vertical markets are analyzed and compared to industry benchmarks for response rates of static direct mail campaigns, to provide a solid base of actual performance data and information.
Published By: Cisco EMEA
Published Date: Nov 13, 2017
Big data and analytics is a rapidly expanding field of information technology. Big data incorporates technologies and practices designed to support the collection, storage, and management of a wide variety of data types that are produced at ever increasing rates. Analytics combine statistics, machine learning, and data preprocessing in order to extract valuable information and insights from big data.
Published By: Cisco EMEA
Published Date: Mar 05, 2018
The competitive advantages and value of BDA are now widely acknowledged and have led to the shifting of focus at many firms from “if and when” to “where and how.” With BDA applications requiring more from IT infrastructures and lines of business demanding higher-quality insights in less time, choosing the right infrastructure platform for Big Data applications represents a core component of maximizing value. This IDC study considered the experiences of firms using Cisco UCS as an infrastructure platform for their BDA applications. The study found that Cisco UCS contributed to the strong value the firms are achieving with their business operations through scalability, performance, time to market, and cost effectiveness. As a result, these firms directly attributed business benefits to the manner in which Cisco UCS is deployed in the infrastructure.
Digital transformation (DX) is a must for midsize firms (those with 100 to 999 employees) to thrive in the digital economy. DX enables firms to increase competitive advantage through initiatives such as automating business processes, creating greater operational efficiencies, building deeper customer relationships, and creating new revenue streams based on technology-enabled products and services. DX is a journey, and it starts with firms embracing an IT-centric vision that guides a data-driven, analytics-first strategy. The outcome of DX initiatives depends on the ability of a firm to efficiently leverage people (talent), process, platforms, and governance to meet the firm’s business objectives.
If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem.
Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.
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.