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data driven report

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By: IBM     Published Date: Jul 17, 2018
With the deadline for GDPR compliance looming in May 2018, it’s a good time for security and privacy professionals to take stock of how their readiness efforts and approaches compare to the rest of the industry. This data-driven report outlines the current state of compliance, trends by industry and geography, and key Forrester recommendations for moving your efforts forward.
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     IBM
By: Group M_IBM Q418     Published Date: Sep 25, 2018
With the deadline for GDPR compliance looming in May 2018, it’s a good time for security and privacy professionals to take stock of how their readiness efforts and approaches compare to the rest of the industry. This data-driven report outlines the current state of compliance, trends by industry and geography, and key Forrester recommendations for moving your efforts forward.
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     Group M_IBM Q418
By: SAS     Published Date: Aug 28, 2018
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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     SAS
By: IBM     Published Date: Jul 07, 2014
Business analytics can empower your business managers to make more fact-based, data-driven decisions that improve operating results. Learn more in a report from Nucleus Research.
Tags : ibm, profitability, analytics, big data, midmarket, midsize companies, data-driven decision making, predictive analytics
     IBM
By: SAS     Published Date: Apr 25, 2017
Organizations in pursuit of data-driven goals are seeking to extend and expand business intelligence (BI) and analytics to more users and functions. Users want to tap new data sources, including Hadoop files. However, organizations are feeling pain because as the data becomes more challenging, data preparation processes are getting longer, more complex, and more inefficient. They also demand too much IT involvement. New technology solutions and practices are providing alternatives that increase self-service data preparation, address inefficiencies, and make it easier to work with Hadoop data lakes. This report will examine organizations’ challenges with data preparation and discuss technologies and best practices for making improvements.
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     SAS
By: SAS     Published Date: Oct 18, 2017
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too. Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data. To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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     SAS
By: Sirius Computer Solutions, Inc.     Published Date: Jul 08, 2014
In today’s data-driven culture, tools for business analysis are quickly evolving. Clients need a solution to accelerate their business analytics and reporting capabilities while lowering OP-Ecosts associated with systems management and cost of ownership. Download to learn more!
Tags : sirius computer solutions, ibm, systems solution, sap business suite, sap hana, data, system management
     Sirius Computer Solutions, Inc.
By: SocialFlow     Published Date: Oct 30, 2014
Research shows that Data-Driven Social Media publishing delivers a 91% increase in reach and a 26% increase in engagement. This report is based on 1.6 M posts on Facebook, Twitter and Google Plus, and proves that how you distribute your social posts is more important to improving your engagement than what you’re posting.
Tags : social media, social media management, social performance, social best practices, social publishing, social media results, earned media, facebook results
     SocialFlow
By: Adobe     Published Date: Apr 15, 2016
If your company is a car, data can change it form a sedan to a Porsche. Data-driven marketing helps you predict what your customers want and deliver it faster and better. Our report, Demonstrating Impact: Pedal to the Metal, outlines five ways data-driven marketing can transform your business into a machine that can leave your competition in the dust. Download our guide to learn how data-driven marketing can help you: • Define the right goals and performance indicators • Make better business decisions faster • Deliver personalized and compelling experiences • Spend budget more profitably • Enhance employee efficiency Download our guide to transform your business.
Tags : adobe, data driven marketing, marketing, business intelligence, market research, traditional marketing
     Adobe
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