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.
A picture is worth a thousand words especially when you are trying to find relationships and understand your data which could include thousands or even millions of variables. To create meaningful visuals of your data, there are some basic tips and techniques you should consider. Data size and composition play an important role when selecting graphs to represent your data. This paper, filled with graphics and explanations, discusses some of the basic issues concerning data visualization and provides suggestions for addressing those issues. From there, it moves on to the topic of big data and discusses those challenges and potential solutions as well. It also includes a section on SASŽ Visual Analytics, software that was created especially for quickly visualizing very large amounts of data. Autocharting and "what does it mean" balloons can help even novice users create and interact with graphics that can help them understand and derive the most value from their data.
This paper provides an introduction to deep learning, its applications and how SAS supports the creation of deep learning models. It is geared toward a data scientist and includes a step-by-step overview of how to build a deep learning model using deep learning methods developed by SAS. Youll then be ready to experiment with these methods in SAS
Visual Data Mining and Machine Learning. See page 12 for more information on how to access a free software trial. Deep learning is a type of machine learning that trains a computer to perform humanlike tasks, such as recognizing speech, identifying images or making predictions. Instead of organizing data to run through predefined equations, deep learning sets up basic parameters about the data and trains the computer to learn on its own by recognizing patterns using many layers of processing. Deep learning is used strategically in many industries.
Published By: SRC,LLC
Published Date: Jun 01, 2009
To mine raw data and extract crucial insights, business decisionâmakers need fast and comprehensive access to all the information stored across their enterprise, regardless of its format or location. Furthermore, that data must be organized, analyzed and visualized in ways that permit easy interpretation of market opportunities growth, shifts and trends and the businessâprocess changes required to address them. Gaining a true perspective on an organization’s customer base, market area or potential expansion can be a challenging task, because companies use so many relational databases, data warehouse technologies, mapping systems and ad hoc data repositories to gather and house information for a wide variety of specialized purposes.
As data center costs continue to rise, green is the word of the day. What it means is cost savings through consolidation and lower energy usage, as this white paper shows. See the role energy consumption plays in today's data centers, and how IBM Tivoli solutions can help optimize energy use in the data center.
Today’s economic climate presents challenges in achieving business differentiation. Investing in innovation during an economic downturn may seem counterintuitive at first, but it can help companies pull ahead of the competition by displaying a show of strength in a climate of weakness. The Microsoft® Application Platform can help organizations do more with less, enabling them to more quickly, efficiently, and cost-effectively deliver custom solutions that provide strong business value.
Managing expectations before, during and after the adoption of visualization software is crucial. Users should know what the rollout process will look like and how it will take place, and have clear goals for using the tool. Make sure that the desired outcome isnt just look-and-feel. Creating beautiful charts and graphs is not a substitute for practical business decisions.
Published By: Datawatch
Published Date: Mar 21, 2014
Big Data is not a new problem. Companies have always stored large amounts of datastructured like databases, unstructured like documentsin multiple repositories across the enterprise. The most important aspect of big data is not how big it is, or where it should be stored, or how it should be accessed. Its the efficacy of business intelligence tools to plumb its depths for patterns and trends, to derive insight from it that will give companies competitive advantage in an increasingly challenging business climate. Visualization allows companies to analyze big data in real-time across a variety of sources in order to make better business decisions.
Visual Patch 2.0 is a fast and efficient solution for software developers and content distributors who need to create software patches. Read through a comprehensive list of features, and learn about the system requirements of Visual Patch 2.0.
Published By: Visualware
Published Date: Sep 21, 2007
It is important to measure the actual data flow of a connection to get a meaningful picture of connection throughput. See how MySpeed measures and reports data transfers, and helps identify performance impacted by network congestion and traffic control.
Published By: Visualware
Published Date: Sep 21, 2007
Connection Speed versus Connection Quality is a crucial issue for measuring bandwidth performance. A fast connection speed by itself can render more application deliver problems (such as VoIP), than a slower connection with consistent throughput.