What if you could use just one platform to detect all types of major financial crimes?
One platform to handle the analytical tasks of fraud detection, including:
Data processing and aggregation
Statistical/mathematical/machine learning modeling
One platform that could successfully reduce complex and time-consuming fraud investigations by combining extremely different domains of knowledge including Business, Economics, Finance, and Law. A platform that can cover payments, credit card transactions, and know your customer (KYC) processes, as well as similar use cases like anti-money laundering (AML), trade surveillance, and crimes such as insurance claims fraud.
Learn more about TIBCO's comprehensive software capabilities behind tackling all these types of fraud in this in depth whitepaper.
Published By: Datastax
Published Date: Oct 11, 2019
The first and most important step to building a successful, scalable application is getting the data model right.
In this white paper, you’ll get a detailed, straightforward, five-step approach to creating the right data model right out of the gate—from mapping workflows, to practicing query-first design thinking, to using Cassandra data types effectively.
Let’s face it: in today’s B2B landscape, the buyers call the shots. Buyers today are proactive, research
their own options, and often include many decision makers rather than just one who can be wooed on
a golf course or over dinner.
So, where does that leave the salesperson? To succeed in this new landscape, sales professionals must
understand how the buyer’s journey has changed and unlock the advantages that data analytics and
statistical modeling can offer. Sales and marketing teams must also learn how to align their efforts to
present a truly coordinated experience.
Read this paper to learn how to take advantage of untapped opportunities for helping sales teams
evolve in today’s buyer-empowered landscape.
Will the people you need for your future workforce be there? This complimentary SuccessFactors white paper shows how to shorten the journey to data-driven decision-making about talent. Download it today.
The focus of modern business intelligence has been self-service; pushing data into the hands of end users more quickly with more accessible user interfaces so they can get answers fast and on their own. This has helped alleviate a major BI pain point: centralized, IT-dominated solutions have been too slow and too brittle to serve the business.
What has been masked is a lack of innovation in data modeling. Data modeling is a huge, valuable component of BI that has been largely neglected. In this webinar, we discuss Looker’s novel approach to data modeling and how it powers a data exploration environment with unprecedented depth and agility.
Topics covered include:
• A new architecture beyond direct connect
• Language-based, git-integrated data modeling
• Abstractions that make SQL more powerful and more efficient
Published By: Datarobot
Published Date: May 14, 2018
The DataRobot automated machine learning platform captures the knowledge, experience, and best practices of the world’s leading data scientists to deliver unmatched levels of automation and ease-of-use for machine learning initiatives. DataRobot enables users of all skill levels, from business people to analysts to data scientists, to build and deploy highly-accurate predictive models in a fraction of the time of traditional modeling methods
In the world of value-based healthcare, your data is the key to extracting the most actionable insights that provide real value to your organization. But getting to those insights can prove difficult, especially if you have to connect disparate data sources. You need transparency into key insights that can help your team make more informed decisions for the success of your organization.
In this listicle, we explore five ways an analytics solution can help you transform your organization through the power of insight. From risk modeling to predictive analytics, utilizing the right mix of analytics can improve patient outcomes and ultimately move your organization closer to your ideal value-based care model
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
When it comes to audience engagement, the landscape has been completely rewritten. Media and entertainment companies need to embrace new technologies to achieve revenue goals. The Adobe guide, Play to Win in Audience Intelligence, shows you how.
Read the guide to learn:
• How to bring your data sources together into a unified view of the customer
• How to move beyond basic demographic attributes to behavior attributes
• How to use look-alike modeling to improve customer targeting and acquisition
Data modeling has evolved from an arcane technique for database designers into an entire family of interrelated techniques that serves many constituencies, including techno-phobic business stakeholders and users. The new maturity of modeling tools and techniques arrives in the nick of time, because new technical and regulatory realities demand that enterprises maintain scrupulous awareness of their data and how it is used. Data modeling is no longer for databases only, no longer for technologists only, and no longer optional.
Today's data centers are embarking down a path in which "old world" business, technology, and facility metrics are being pushed aside in order to provide unparalleled service delivery capabilities, processes, and methodologies. The expectations derived from today’s high-density technology deployments are driving service delivery models to extremes with very high service delivery capabilities adopted as baseline requirements within today’s stringent business models. Part of the "revolution" that is driving today's data center modeling to unprecedented high performance and efficiency levels is the fact that computer processing advances with regard to high-performance and smaller footprints have truly countered each other.
Published By: Anaplan
Published Date: Mar 29, 2018
Incentive compensation represents the potential of delivering optimal sales results. But with up to 60% of sales reps’ income coming from incentive comp, it is crucial to get this right. Our study data has shown that ineffective compensation structures can lead to disengaged reps, high turnover, money left on the table, and low margins. The way we have designed and managed incentive compensation plans in the past may inhibit the sales force and prevent the business from scaling at the needed rate. Modeling and planning quickly become too complex for a spreadsheet-driven exercise.
Published By: iKnowtion
Published Date: Nov 17, 2011
This highly successful dot-com brand leveraged its customer information assets to understand the broad range of customers attracted to its product offering, as well as how to evaluate each customer's future value potential.
Published By: Quantcast
Published Date: Jul 16, 2013
Increased competition in a world of growing and complex data requires tremendous resourcefulness to both find and implement scalable ways to grow your business. Using sophisticated data modeling coupled with real-time media buying, US Cellular was able to reduce their CPA to 46% below the campaign average. Read how big data works to drive customer acquisition in the complete success story.
A powerful signal integrity analysis tool must be flexibility, easy to use and integrated into an existing EDA framework and design flow. In addition, it is important for the tool to be accurate enough. This report reviews a validation study for the Mentor Graphics HyperLynx 8.0 PI tool to establish confidence in using it for power integrity analysis.
For advanced signaling over high-loss channels, designs today are using equalization and several new measurement methods to evaluate the performance of the link. Both simulation and measurement tools support equalization and the new measurement methods, but correlation of results throughout the design flow is unclear. In this paper a high performance equalizing serial data link is measured and the performance is compared to that predicted by simulation. Then, the differences between simulation and measurements are discussed as well as methods to correlate the two.
This whitepaper looks at why companies choose Riak
over a relational database. We focus specifically on
availability, scalability, and the key/value data model. Then
we analyze the decision points that should be considered
when choosing a non-relational solution and review data
modeling, querying, and consistency guarantees. Finally, we
end with simple patterns for building common applications
in Riak using its key/value design, dealing with data conflicts
that emerge in an eventually consistent system, and discuss
The intrepid data miner runs many risks, including being buried under mountains of data or disappearing along with the "mysterious disappearing terabyte." This article outlines some risks, debunks some myths, and attempts to provide some protective "hard hats" for data miners in the technology sector.
Published By: SPSS, Inc.
Published Date: Mar 31, 2009
The intrepid data miner runs many risks, including being buried under mountains of data or disappearing along with the "mysterious disappearing terabyte." This article outlines some risks, debunks some myths, and attempts to provide some protective "hard hats" for data miners in the marketing sector.
By using the Oracle Exadata Database Machine as your data warehouse platform you have a balanced, high performance hardware configuration. This paper focuses on the other two corner stones, data modeling and data loading.
AdRoll looked in detail at the attribution strategies that agencies and brands across these markets are employing to find out how well they are leveraging their data to attract, convert and grow their customer base, as well as the challenges they face in integrating attribution into their marketing. From all of this AdRoll and Econsultancy deliver key insights and actionable insights which you can apply to your business in implementing or optimising attribution modeling.
This white paper outlines the components of the Banking Data Warehouse (BDW) and how they assist financial institutions in addressing the data modeling and data consolidation issues relating to the SOX regulations.