October 23 - 24, 2017
The W, San Francisco, CA
5 Key Strategies for Developing Enterprise Data Governance
The latest from FIMA in partnership with Informatica, this report outlines the keys to drawing a blueprint for an effective enterprise data governance practice. Download your copy by clicking the image to the left!
FIMA West 2016 Preliminary Attendee List
Want a preview of who you'll meet onsite at FIMA West 2016?Download the preliminary attendee list now by clicking the picture to the left or the link above. Updated Oct. 19
Modernizing Data Quality & Governance: Unlock Performance & Reduce Risk
Good data quality is absolutely essential to help financial services companies minimize risk while better informing business decisions. Unfortunately for many of these organizations, data quality tools that were purchased for IT to fix data issues have not keep pace with the ascendance of data governance programs that require business and IT to co-manage the quality of data as a business asset. FIMA's latest whitepaper evaluates how financial services companies are managing the challenges posed by data quality management. By analyzing which data types and data characteristics businesses are struggling with, it uncovers the true business costs associated with data quality. It will also gauge how data governance programs are maturing and how they are being measured. Finally, it assesses how data is being managed within financial institutions. Click the banner to the left to download the full whitepaper!
Creating Smart Data Insights Through Intelligent Data Integration: A FactSet Whitepaper
As costs of data storage decrease and applications that would have been impossible become feasible, there is a growing imperative on financial institutions to take control of their siloed data and bring it into a new "smart data" paradigm. Produced in conjunction with FactSet, this report covers: - The challenges of creating data insights - Nuances present in tagging data for integration and compliance - How regulations like BCBS 239 are guiding firms towards better big data analytics
Transforming Financial Institutions Through Data Governance
Although data management practices have been around almost since the inception of the computer, data governance has only become a central strategic priority for financial institutions over the past few years. The catalysts for this relatively novel emphasis on data governance are rooted in two of the financial industry’s most fundamental values: minimizing risk and enhancing value from business intelligence. First-rate data governance serves both of these interests, mitigating the regulatory and financial risks associated with data mismanagement while also opening up new opportunities for organizations to leverage data to make more informed business decisions. Put simply, effectively managed data can be an organization’s greatest asset; this is the importance of good data governance. Click on the image to the left to download.
Charting the Maturity of the Information Practice as a Driver of Business Transformation
Paxata and FIMA partnered in Q2 2017, delivering a benchmark survey to gain a better understanding of how financial data management and governance are progressing as disciplines. Many firms have made the decision to invigorate their data practices to be able to strategically outpace whatever material or theoretical demands might fall upon them. With the development of these capabilities, a new focus for the data practice is also emerging. Adopting the trend of "self-service" data tools has helped find the value in many organization's data practices.
Inflection Point: Innovating Business Enablement, Data Access and Reporting in Finance
The finance industry is at an inflection point with NoSQL databases. Experts predict a breakthrough in the near future, one that will solidify its status as a business enabler. But data management functions need to prove their value by delivering relevant and timely data that empowers business users.This 2018 FIMA AI Report investigates how these companies are realizing the future of financial data management through using big data, cloud, and NoSQL database adoption. Discover why this has become a top priority for data management teams—for efficiency, longevity, and growth.