To survive and thrive in an era of accelerating digital
disruption, organizations require accessible data,
actionable insights, continuous innovation, and
disruptive business models. It’s no longer enough to
prioritize and implement analytics – leaders are being
challenged to stop doing analytics just for analytics’
sake and focus on defined business outcomes.
In addition, these leaders are being challenged to
bring predictive capabilities and even prescriptive
recommended actions into production at scale. As AI
and accelerated growth and transformation become
top of mind, many enterprises are realizing that their
current segmented analytics approach isn’t built to last,
and that real transformation will require proper endto-
end data management, data security, and a data
processing platform company-wide. The year 2019 will
be a turning point for many organizations that realize
being data-driven doesn’t guarantee future success.
This whitepaper details how predictive analysis can help your business. Predictive analytics help you make better, faster decisions, giving your organization a significant competitive advantage in the technology sector.
Published By: SPSS, Inc.
Published Date: Mar 31, 2009
This whitepaper details how predictive analysis can help your business. Predictive analytics help you make better, faster decisions, giving your organization a significant competitive advantage in the marketing sector.
Published By: TruSignal
Published Date: Jun 03, 2013
This white paper aims to provide B2C digital marketers with a better understanding of why you may need an audience expansion technique and what questions to ask yourself before you get started. We hope to not only build an imperative for audience expansion techniques, but also to offer a guide that will help you choose the right data and right techniques for reaching more of your desired prospects online. Specifically, this white paper will discuss and differentiate two specific expansion approaches: lookalike and act-alike audiences including how they are built, the problems they solve and how to use them effectively throughout the marketing funnel.
collectd is an open source daemon that collects system and application performance metrics. With this data, collectd then has the ability to work alongside other tools to help identify trends, issues and relationships not easily observable.
Read this e-book to get a deep dive into what collectd is and how you can begin incorporating it into your organization’s environment.
Imagine a world where incident alerts arrive 30 minutes before problems even begin — you’d actually have the power to prevent outages and deliver a truly seamless experience to your customers. Sound impossible? Think again — the right AIOps (Artificial Intelligence for IT Operations) solution can help you maintain uptime, reduce manual incident-management tasks and increase productivity.
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
Tax fraud is already prevalent, and fraudsters are more sophisticated and automated than ever. To get ahead of the game in detecting fraud
and protecting revenue, tax agencies need to leverage more advanced and predictive analytics. Legacy processes, systems, and attitudes
need not stand in the way. To explore the challenges, opportunities, and value of tax fraud analytics, IIA spoke with Deborah Pianko, a
Government Fraud Solutions Architect within the SAS Security Intelligence practice.
Creating predictive analytics from alternative data has become the current focus of the biggest quant trading firms in the industry
The democratization of financial services data and technology, together with more intense competition, makes the needs of today’s market participants vastly different from those of previous generations. Firms must locate untapped sources of data for both public and non-public companies. This alternative data, such as payment data and other non-public information, from sources beyond the common channels, can be a predictive indicator of market performance; a difference maker in assisting firms as they develop models to evaluate their investments.
By combining our unique data sets with advanced analytics, traders, analysts and managers can seek predictive signals and actionable information utilizing their own models.
View our research report to learn how alternative data, our 'Information Alpha,' can help you earn differentiated investment returns.
Applications are the engines that drive today’s digital businesses. When the infrastructure that powers those applications is difficult to administer, or fails, businesses and their IT organizations are severely impacted. Traditionally, IT assumed much of the responsibility to ensure availability and performance. In the digital era, however, the industry needs to evolve and reset the requirements on vendors.
HPE Nimble Storage has broken away from convention and transformed how storage is managed and supported with the HPE InfoSight predictive analytics platform. HPE engaged ESG to conduct a quantitative survey of the HPE Nimble Storage installed base, as well as non-HPE Nimble Storage customers, to better assess how HPE InfoSight positively impacts customer environments.
To find out more download this whitepaper today.
In a competitive landscape that favors the fastest and the smartest, financial services firms that invest in building sophisticated insight and predictive analytics will be better positioned to emerge as market leaders.
This video demonstrates how IBM’s Behavior Based Customer Insight for Banking leverages predictive analytics to help you personalize customer engagement and deliver customized actions. The solution leverages advanced predictive models to analyze customer transactions and spending behavior to more deeply understand customer needs and propensities, anticipate life events, and help provide a unique customer experience.
This paper will outline the value and methods involved in data mining across both quantitative and qualitative data. In addition, it will describe the data transformations necessary before doing such work, and the tools that are particularly valuable for mining mixed data types.
Learn what criteria distinguished certain companies as top performers within the SMB sector, the factors to consider when assessing your organization's BI competency and the required actions to achieve best-in-class performance.
This white paper discusses how IBM InfoSphere can support the integration and governance of Big Data in healthcare. The white paper reviews three case studies including predictive analytics with Electronic Medical Records, time series data in a neonatal intensive care unit and predictive pathways for disease.
Published By: BlackLine
Published Date: Aug 06, 2018
The biotechnology and pharmaceutical industry is among the most heavily regulated industries in the world, challenged by evolving regulations, complex compliance requirements and close regulatory scrutiny. At the same time, companies must address the market pressures of globalization, the use of predictive data analytics and digital technologies, and the industry’s ongoing consolidation. In this challenging environment, confidence in internal controls is crucial.
Watch this video to see how Denmark’s leading retailer, Coop Danmark, is using predictive analytics and real-time data access to understand customer demand and make more profitable merchandising decisions.
Predictive analytics transforms organizations. Watch this video to see how predictive analytics can improve outcomes in four strategic areas critical to the success of your business:
- Customer satisfaction and retention
- More effective HR processes
- Fraud and threat detection and prevention
- Revenue growth and profitability