Published By: Gladson
Published Date: Aug 25, 2010
Informational Retailing - transformation of shoppers taking control of the way that they research, select and buy products by using a diverse array of sources to gather product information when and where they want it.
Optimization is the key to delivering ever-increasing ROI, with flat or declining marketing budgets. In this whitepaper, learn best practices for optimizing your marketing activities, and do more with less.
We often hear about how the massive volumes of data the US government collects hold a treasure trove of answers to our most challenging questions – be it on population health,
national security, education or how to recoup losses from tax fraud. If only the government could figure out how to make use of all that information.
Texas is one example of a government that is using analytics to solve complex problems. As the case studies here demonstrate, agencies and academia in the Lone Star State are putting big data and analytics to work to eliminate waste, improve productivity and, in some cases, even enhance transparency.
The synergy of creative work and powerful analytics is the route to impactful, innovative campaigns for iris Worldwide, the global creative innovation network. iris has made this strategy a reality using the advanced analytics capabilities offered by SAS, which has given the agency the ability to garner deeper insights using larger data sets, ultimately resulting in higher returns for its customers.
The large array of connected devices, often referred to as the “Internet of Things” (IoT), is delivering an array of new data from the sensors they contain. This data offers the promise of new services, improved efficiency and, possibly, more competitive business models.
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.
Ecclesiastical uses SAS® to improve data quality to make better decisions that enhance the reputation of the business, affect millions of pounds of risk selection/underwriting and help to establish optimum reinsurance levels.
Millions of pounds hang on decisions around reinsurance and risk selection. Achieving the best possible outcome means taking data and turning it into ‘decision-making gold’. The key is to have good data going into the process.
ITS technology is a general term. Two common and related forms of ITS communication technology using event stream processing are referred to as vehicle-to-vehicle (V2V) and vehicle to-infrastructure (V2X) in the US, and car-to-infrastructure (Car2X) in Europe. The two types of connected-car research and development programs often overlap and can be integrated. Car2X enables vehicle communication with the road transportation infrastructure and provides the ability to send or receive local information about traffic conditions, geo-markers (e.g. to identify pothole locations), road hazards, alerts, safety vehicles, etc. V2V focuses on connected-car technology and the anonymous communication of sensor data continuously transmitted to and from cars. Using event stream processing, this streaming data enables the real-time synthesis of information to communicate what will improve and promote driver safety, reduce crashes, and improve vehicle transportation efficiency.
How does marketing compare to a game of pool? Sometimes you hit a good shot – 9 ball corner pocket – like when you’ve marketed a product and your customer purchases it. But sometimes your shot misses, and you knock in your opponent’s ball. You could even knock your ball into the pocket, but mistakenly knock your opponent’s ball into a different pocket at the same time.
Of course, you can’t predict everything in a game of pool – or in
marketing. A campaign may reveal a weakness that sends
customers scuttling to a competitor. A new product can
cannibalize an existing product line. Customers could leave one
of your legacy product lines to consume one of your newly
launched products – perhaps causing you to lose some
But unlike pool, it’s hard to observe and measure with the naked eye what’s happening in marketing. The way to improve your chances of success is to build a solid measurement plan that lets you define and measure diagnostic metrics.
The financial collapse of 2008 had the greatest impact on the financial services industry since World War II, resulting in consolidation and extensive regulation. The crisis coincided with increased competition from emerging economic powers, nonbanks and fintech organizations. Consumer behavior, from the adoption of mobile banking to P2P payments, forced banks to retool and respond with innovative products and investments in new delivery channels. Technology changed rapidly as well. In the capital markets, trading became fully automated, with pricing, risk decisions and settlement across exchanges made in milliseconds
Imagine that you are in a meeting with several department heads discussing issues around enrollment. As people begin to share their thoughts, you quickly realize that each person in the room is working from conflicting information – and everyone thinks their information is correct. The group spends most of the meeting arguing over whose data and reports are correct rather than understanding the problem and making decisions. Sound familiar? When organizations have their data fragmented across many systems and departments, these situations are all too common. Without a single, trusted source of truth and easyto- use tools to interpret and understand the data, conversations are limited by everyone’s departmental perspectives and resources.
New analytics tools and services are helping organizations extract exceptional business value from the massive volumes of available data provided by various internal and external sources. Many companies are harnessing these insights to improve operational and business processes, troubleshoot problems, identify business opportunities, and generally compete and innovate better. Now the benefits of analytics in those areas are prompting companies to look to analytics to improve information security. Enterprise security organizations are under tremendous pressure to change. Traditional perimeter-focused security controls and strategies have proved inadequate against modern, highly targeted attack campaigns.
Identifying the best technology to improve marketing performance is a complex decision, especially for a growing marketing organization. Deciding where to spend valuable capital should be based on the greatest opportunity for gain. In the current marketing environment, the greatest opportunity is in analytically enabled marketing.
On an average day, 78 Americans die from opioid overdose. Last year’s total was almost 30,000 deaths, roughly two-thirds involving prescription opioids (including Percocet, Vicodin, Hydrocodone, Oxycodone, Oxycontin), the rest involving heroin. The United States, with about 5 percent of the global population, consumes 80 percent of the prescription opioids. The problem affects people of all backgrounds and across the socioeconomic spectrum; the Center for Disease Control (CDC) has officially declared it an epidemic.
Today’s customer experience requires a combination of individualized insights, connected interactions and an agile approach to meet customers in the channel of their choosing. This means more than simply doing the same things over in the new channels. It requires new ways of exploring customer trends and preferences, and being smarter about responding to these factors.
Data visualization is the visual and interactive exploration and graphic representation of data of any size, type (structured and unstructured) or origin. Visualizations help people see things that were not obvious to them before. Even when data volumes are very large, patterns can be spotted quickly and easily. Visualizations convey information in a universal manner and make it simple to share ideas with others.
No matter the vintage or sophistication of your organization’s data warehouse (DW) and the environment around it, it probably needs to be modernized in one or more ways. That’s because DWs and requirements for them continue to evolve. Many users need to get caught up by realigning the DW environment with new business requirements and technology challenges. Once caught up, they need a strategy for continuous modernization.
From midsize companies and government organizations to global banks and professional sports teams, all types of organizations are using data visualization to help make sense of their data and to comprehend information quickly. Keep reading to learn how six organizations of all types and sizes are using data visualization to improve customer relationships, fight fraud and more.
Whether you call them customers, clients, patrons, guests or patients, customers are your organization’s most important asset. And that means customer loyalty should be among your top priorities. No matter when or where the customer journey begins – from websites and online chat to physical locations and call centers – customers expect you to provide a unique and personal experience. How can you use data and analytics to recognize your best customers across channels and know exactly where they are in their customer journey? Keep reading to find out.
As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment.
A paradigm shift is underway in the cybersecurity industry. Cybersecurity professionals are moving from a focus on attacker prevention to attacker detection. Preventing the “bad guys” from getting in is still important, but cyber adversaries are increasingly able to bypass even the most sophisticated network defenses. Once inside, it is more important than ever to find these attackers fast, before their activities get buried in the daily volume and pulse of network communications. This is where security analytics holds promise. Security analytics provides the necessary and timely visibility into normal and abnormal network behavior. This visibility enables devices and entities acting suspiciously to be quickly identified and investigated.
The Internet of Things (IoT) – devices and sensors connected to computing systems and networks – has received enormous attention in the last few years. The attention is due, in part, to the proliferation of connected devices, from about a million in the early 1990s to more than five billion today. In addition, the technology for connecting the devices has become more affordable and easier to integrate. The result is that IoT is helping to digitize more and more business processes, from the factory floor to tracking shipments across oceans. Digitized processes are providing a continuous stream of digital data. By analyzing the data stream, businesses can refine their processes by better understanding how those processes are performing, identifying possible issues sooner and uncovering areas for improvement.
Hype and hope — Big Data has generated a lot of both. Thanks to an abundance of enterprise information systems, networks, applications and devices that churn out huge volumes of information, government agencies are awash in Big Data. Add to this data growth the emerging trend of the Internet of Things (IoT) — the network of people, data, things and processes that is increasingly linked through automated connections and sensors — and the future of Big Data can seem quite daunting.