Cardlytics, a transaction-driven marketing™ company, focused on tracking and understanding consumer buying behavior and delivering actionable intelligence, has been undergoing tremendous growth, ramping up from 10,000 pilot customers to its current reach of 70 million households. Founded in 2008 and based in Atlanta, Georgia, Cardlytics partners with financial institutions such as Bank of America, PNC Bank, Regions Bank and Fiserv.
As the data created and consumed by users worldwide continues to double every two to four years, the role of scale-out file systems and policy-based data management solutions such as Quantum's StorNext is becoming critical to managing this growth and streamlining data workflows.
Click streams, social media, log files—a growing mountain of valuable data looms above you. You’ve taken countless steps to capture and utilize your company’s structured data, but despite your efforts, it seems you have made no progress in the arduous trek to the summit. You know that there is a wealth of lucrative business information waiting for you at the top, but how can you possibly reach it when the mountain of data is growing before your very eyes?
Data warehousing is a success, judging by its 25 year history of use across all industries. Business intelligence met the needs it was designed for: to give non-technical people within the organization access to important, shared data. The resulting improvements in all aspects of business operations are hard to dispute when compared to the prior era of static batch reporting.
No doubt the amount of data your company collects is growing. But what’s the point of amassing all that information if you can’t use it to drive your business forward? Smart businesses are giving people throughout their organizations access to deeper intelligence by marrying their big data and business intelligence efforts into a big data solution. The result is better decisions based on meaningful insights company wide. What’s your strategy for big data analytics?
This technical brief is designed to provide a background and detailed level of understanding for those analyzing a move from a relational database to a NoSQL model (specifically emphasizing the Riak key/value store offered by Basho).
Multi-datacenter replication is a critical part of modern infrastructure, providing essential business benefits for enterprise applications, platforms, and services. Riak Enterprise offers multi-datacenter replication features so that data stored in Riak can be replicated to multiple sites. With Riak Enterprise, data can be replicated across locations and geographic areas, providing disaster recovery, data locality, compliance with regulatory requirements, the ability to “burst” peak loads into public cloud infrastructure, and more.
By now, we have all heard the claims. Data is the new oil. Big data is different. Big data is a management revolution. Big data is the next frontier for innovation, competition, and productivity. Big data makes the scientific method obsolete.
The desire for new big data analytics capabilities is driving a wave of expert recommendations for cooperative analytic processing architectures, where processing is shared between several integrated systems. Experts have also identified a new breed of system, the analytic platform, which coordinates analytic processing across these next-gen architectures. In this paper, learn more about experts’ new architectural recommendations, read criteria for analytic platforms – and find out why ParAccel’s analytic platform is the leading example of this next wave of analytic systems.
Harvard Business Review says 2.5 exabytes (billion gigabytes) of data are created every day.1 It’s no wonder. In that same day, Facebook users share 1 billion pieces of content, and Twitter users generate more than 200 million tweets. Two million users access the Internet to search and buy, leaving behind click streams, comments, and product reviews. Corporate data has also blossomed to almost unmanageable volumes. Walmart processes more than 1 million customer transactions every hour.2 And smaller enterprises roll out new applications in every part of their business, each of which collects vast amounts of new information. So much data is available that the information technology (IT) industry has spawned a new term to describe it: “Big Data.”
Companies have been striving to harness and leverage the power of their data assets for decades. Now major U.S. corporations and government agencies are finally realizing business value from Big Data. That is the finding of a survey and series of follow-up interviews conducted by NewVantage Partners with C-level executives and function heads representing companies and government agencies during the second half of 2012.
"Big Data " initiatives create significant opportunities for business and IT leaders, but both must come to terms with challenges they introduce. A focus on the impact of analytical outcomes in supporting material and measurable business decisions.
The concept of “big data” is gaining attention across industries and the globe, thanks to the growth in social media (Twitter, Facebook, blogs, etc.) and the explosion of rich content from other information sources (activity logs from the Web, proximity and wireless sources, etc.). The desire to create actionable insights from the ever- increasing volumes of unstructured and structured data sets is forcing enterprises to rethink their approaches to big data, particularly as traditional approaches have proved difficult- if even possible- to apply to structured data sets.
To ensure widespread adoption of business intelligence (BI) practices, Organizations have been increasingly deploying state-of-the-art tools and techniques. However, most of these initiatives have met with little success. Why? One reason: The majority of BI systems have been designed on the basis of how technology approaches a problem. However, BI technology rarely meets its objective of aiding human cognition of a particular business scenario. Even the improvements in technology have not helped to increase BI adoption, because lost in the pursuit of technological excellence is a lack of focus on user behavior.
There is a new universe of data being created by smart meters, mobile devices, social media, RFID, web logs, and other sources. Meanwhile, many industries have only begun exiting the paper-based documentation era. It’s no longer the case that all possible insights about an organization come only from a structured data warehouse full of vetted data developed inside one’s own four walls. Embracing big data means accepting that you can gain valuable insights about your organization, your customers, and the world at large from external sources, and by looking at data in a new way.
I am pleased that NewVantage Partners conducted this survey and made the results available to me for review prior to publication. There is a lot of interest in the topic of Big Data as evidenced by the high response rate to the survey. The survey yielded some interesting findings, many of which are relevant to research I have conducted.
Financial markets are rarely predictable. What moves a price one day might have no effect the next, or it might be felt several steps away from where it’s expected. That’s where market sensing plays a role. Broadly defined, Market Sensing is the ability to bring as much relevant information as possible, to bear on trading and risk decision-making.
The power of zoom represents an evolution in the way government sees and interacts with the world. When location data is coupled with existing government data and expertise, every point on the map can provide historical and predictive perspective to inform complex policy decisions. The map itself has been transformed from a static picture to a living platform for shared decision making and real-time collaboration, focusing the energy of the crowd and empowering government and citizens to work together to respond quickly to challenges at any scale.
According to TDWI Research’s 2011 Big Data Analytics Survey, 33% of surveyed organizations are contemplating a replacement of their analytic databases, data warehouses, and similar platforms to keep pace with new and intensifying requirements for advanced analytics in a “big data” world. As user organizations make such platform replacements—or add additional platforms to their expanding data warehouse architectures—they are turning more and more to specialized analytic database management systems (DBMSs).
In this one-on-one interview, Rich Brueckner, President of insideHPC, discusses big data challenges and opportunities, as well as what technologies will help companies deal with their growing amounts of data. InsideHPC is a CIO Summit, CIO Cloud Summit, and CIO Life Sciences Summit event partner.