data analyst

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Lessons from B2B Leaders in Managing Data

Published By: Dun & Bradstreet     Published Date: Feb 21, 2017
As the volume of data coming into organizations – from both internal and external sources – continues to grow and makes its way across departmental systems in many different formats, there is a critical need to create a single, holistic view of the key data entities in common use across the enterprise. Master Data Management (MDM) aims to accomplish this goal. Not surprisingly, MDM has become a significant priority for global enterprises, with the market expected to triple from $9.4B to $26.8B by 2020 according to analysts. The reality, though, is that while seemingly everyone is investing heavily in the tools to manage data, few are putting a great enough emphasis on the data itself. And that’s a problem. Poor data quality is said to be costing businesses $3.1 trillion annually – and that’s just in the US alone. The information being put into MDM tools must be mastered first and foremost.
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managing data, data management insight, mdm, master data management
    
Dun & Bradstreet

Unlocking Customer Insights with Machine Learning

Published By: Q2 eBanking     Published Date: Jul 30, 2017
Many financial institutions see their customer data as one of their most valuable assets. Unlocking insights from that data helps FIs understand, anticipate and offer account holders the products and services they truly need. A major trend to unlocking customer insights is using machine learning to surface the behavioral intelligence buried in the large amount of account holder transactional data captured each and every day. In this paper, learn how a group of talented, enthusiastic analysts with an open approach to data can yield some very interesting and extremely valuable and actionable results. This approach, championed by Q2 Executive Vice President and CTO Adam Anderson, has led to a new platform, Q2 SMART, which provides powerful behavioral analytics for financial institutions, enabling growth while providing account holders with real value.
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Q2 eBanking

Six Reasons to Upgrade Your Database

Published By: Group M_IBM Q1'18     Published Date: Jan 08, 2018
Effectively using and managing information has become critical to driving growth in areas such as pursuing new business opportunities, attracting and retaining customers, and streamlining operations. In the era of big data, you must accommodate a rapidly increasing volume, variety and velocity of data while extracting actionable business insight from that data, faster than ever before. These needs create a daunting array of workload challenges and place tremendous demands on your underlying IT infrastructure and database systems. This e-book presents six reasons why you should consider a database change, including opinions from industry analysts and real-world customer experiences. Read on to learn more.
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database, streamlining, it infrastructure, database systems
    
Group M_IBM Q1'18

Empowering the Automotive Industry through Intelligent Orchestration

Published By: Group M_IBM Q119     Published Date: Feb 15, 2019
With the increasing complexity and volume of cyberattacks, organizations must have the capacity to adapt quickly and confidently under changing conditions. Accelerating incident response times to safeguard the organization's infrastructure and data is paramount. Achieving this requires a thoughtful plan- one that addresses the security ecosystem, incorporates security orchestration and automation, and provides adaptive workflows to empower the security analysts. In the white paper "Six Steps for Building a Robust Incident Response Function" IBM Resilient provides a framework for security teams to build a strong incident response program and deliver organization-wide coordination and optimizations to accomplish these goals.
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Group M_IBM Q119

Delivering Hybrid Analytics at the Speed of Business: IBM Integrated Analytics System

Published By: Group M_IBM Q2'19     Published Date: Jul 01, 2019
This white paper considers the pressures that enterprises face as the volume, variety, and velocity of relevant data mount and the time to insight seems unacceptably long. Most IT environments seeking to leverage statistical data in a useful way for analysis that can power decision making must glean that data from many sources, put it together in a relational database that requires special configuration and tuning, and only then make it available for data scientists to build models that are useful for business analysts. The complexity of all this is further compounded by the need to collect and analyze data that may reside in a classic datacenter on the premises as well as in private and public cloud systems. This need demands that the configuration support a hybrid cloud environment. After describing these issues, we consider the usefulness of a purpose-built database system that can accelerate access to and management of relevant data and is designed to deliver high performance for t
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Group M_IBM Q2'19

Six Steps for Building a Robust Incident Response Function

Published By: Group M_IBM Q4'19     Published Date: Sep 17, 2019
With the increasing complexity and volume of cyberattacks, organizations must have the capacity to adapt quickly and confidently under changing conditions. Accelerating incident response times to safeguard the organization's infrastructure and data is paramount. Achieving this requires a thoughtful plan- one that addresses the security ecosystem, incorporates security orchestration and automation, and provides adaptive workflows to empower the security analysts. In the white paper ""Six Steps for Building a Robust Incident Response Function"" IBM Resilient provides a framework for security teams to build a strong incident response program and deliver organization-wide coordination and optimizations to accomplish these goals.
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Group M_IBM Q4'19
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