big data analytics

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Big Data Comes of Age

Published By: Teradata     Published Date: Feb 26, 2013
This survey and research report discusses shifts in the data management landscape and the movement to align data with operational and analytical workloads creating the best possible unified data architecture platform. Read on to learn more.
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big data, survey report, data management, landscape, movement, align data, operational and analytics workloads, business intelligence, terdata, business technology, data center
    
Teradata

Evolution of Big Data Analytics: Experiences with Teradata Aster and Apache Hadoop

Published By: Teradata     Published Date: Feb 26, 2013
This report explores the evolution of big data analytics and its maturity within the enterprise. It discusses the approaches and economics to using a Discovery platform and Apache Hadoop within the same unified analytical architecture.
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big data analytics, experiences with teradata, apache hadoop, analytics, discovery platform, apache hadoop, teradata, it management, data management, business technology, data center
    
Teradata

Harnessing the Value of Big Data Analytics

Published By: Teradata     Published Date: Feb 26, 2013
Business Insights Using Hadoop with SQL Analytics. Harness the value of big data analytics -- This report discusses a unified data architecture solution providing valuable insight from new and existing data.
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power of analytics, harnessing the value of big data, business intelligence, teradata, unified data architecture, it management, data management, business technology, data center
    
Teradata

Forbes Insights and Turn - The Promise of Privacy

Published By: Turn     Published Date: Mar 27, 2014
In this study from Forbes Insights and Turn, learn what privacy means to marketers and consumers.
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turn, forbes insights, privacy, big data, marketing, advertising, marketing solutions, security, digital marketing, marketing insights, software platform, cross-channel, analytics, application security
    
Turn

Solving the Big Data Intention-Deployment Gap

Published By: BlueData     Published Date: Aug 19, 2015
Big Data is on virtually every enterprise’s to-do list these days. Recognizing both its potential and competitive advantage, companies are aligning a vast array of resources to access and analyze this strategic asset. However, despite best intentions, the majority of these Big Data initiatives are either extremely slow in their implementation or are not yielding the results and benefits that enterprises expect. Download this white paper to learn how to solve the Big Data intention-deployment gap and see how you can make your infrastructure in a flexible, easy-to-use platform that will provide in-depth analytics.
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big data, big data intention-deployment, in-depth analytics, hadoop, data management, data center
    
BlueData

ESG Analyst Report: Big Data Infrastructure Made Easy How to Simplify & Accelerate Hadoop Deployment

Published By: BlueData     Published Date: Aug 19, 2015
As companies seek to better understand their customers, their opportunities, and themselves, they are embracing new technologies such as Hadoop and NoSQL to better manage and manipulate their data. Yet a complete solution for big data has many moving parts while at the same time these moving parts are continuously evolving. Download this white paper to figure out how to make all the moving parts work smoothly together and see how this will ease frustration with business users and free up your IT teams time to handle other issues.
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big data infrastructure, hadoop deployment, spark, analytics software, big data, data management, data center
    
BlueData

Modern Data Warehousing on AWS

Published By: AWS     Published Date: Aug 20, 2018
A modern data warehouse is designed to support rapid data growth and interactive analytics over a variety of relational, non-relational, and streaming data types leveraging a single, easy-to-use interface. It provides a common architectural platform for leveraging new big data technologies to existing data warehouse methods, thereby enabling organizations to derive deeper business insights. Key elements of a modern data warehouse: • Data ingestion: take advantage of relational, non-relational, and streaming data sources • Federated querying: ability to run a query across heterogeneous sources of data • Data consumption: support numerous types of analysis - ad-hoc exploration, predefined reporting/dashboards, predictive and advanced analytics
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AWS

A Pure Primer: AI, Analytics and the Future of Your Enterprise

Published By: Pure Storage     Published Date: Dec 05, 2018
Data is the new currency. Is your organization capitalizing on the full potential of data analytics? In this big data primer, you will learn about the 3 key challenges facing organizations today: managing overwhelming amounts of data, leveraging new complex tools/technologies, and developing the necessary skills and infrastructure. And since storage is where your organization's data lives, it’s a pivotal part of the infrastructure jigsaw puzzle. Thus with a “tuned for everything” storage solution that is purpose-built for modern analytics, you can confidently harness the power of your data to drive your enterprise forward.
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Pure Storage

How to Enable High-Performance ELT Processing

Published By: Amazon Web Services     Published Date: Sep 05, 2018
Big data alone does not guarantee better business decisions. Often that data needs to be moved and transformed so Insight Platforms can discern useful business intelligence. To deliver those results faster than traditional Extract, Transform, and Load (ETL) technologies, use Matillion ETL for Amazon Redshift. This cloud- native ETL/ELT offering, built specifically for Amazon Redshift, simplifies the process of loading and transforming data and can help reduce your development time. This white paper will focus on approaches that can help you maximize your investment in Amazon Redshift. Learn how the scalable, cloud- native architecture and fast, secure integrations can benefit your organization, and discover ways this cost- effective solution is designed with cloud computing in mind. In addition, we will explore how Matillion ETL and Amazon Redshift make it possible for you to automate data transformation directly in the data warehouse to deliver analytics and business intelligence (BI
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Amazon Web Services

Getting Started with Amazon Redshift – Best Practices

Published By: Amazon Web Services     Published Date: Sep 05, 2018
Today’s businesses generate staggering amounts of data, and learning to get the most value from that data is paramount to success. Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on-demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Amazon Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. Organizations choose Amazon Redshift for its affordability, flexibility, and powerful feature set: • Enterprise-class relational database query and management system • Supports client connections with many types of applications, including business intelligence (BI), reporting, data, and analytics tools • Execute analytic queries in order to retrieve, compare, and evaluate large amounts of data in multiple-stage operations
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Amazon Web Services

Optimizing Amazon Redshift, A Real-World Guide

Published By: Amazon Web Services     Published Date: Sep 05, 2018
Just as Amazon Web Services (AWS) has transformed IT infrastructure to something that can be delivered on demand, scalably, quickly, and cost-effectively, Amazon Redshift is doing the same for data warehousing and big data analytics. Redshift offers a massively parallel columnar data store that can be spun up in just a few minutes to deal with billions of rows of data at a cost of just a few cents an hour. It’s designed for speed and ease of use — but to realize all of its potential benefits, organizations still have to configure Redshift for the demands of their particular applications. Whether you’ve been using Redshift for a while, have just implemented it, or are still evaluating it as one of many cloud-based data warehouse and business analytics technology options, your organization needs to understand how to configure it to ensure it delivers the right balance of performance, cost, and scalability for your particular usage scenarios. Since starting to work with this technolog
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Amazon Web Services

Getting Real About Management and “Big Data”

Published By: EMC Corporation     Published Date: Aug 05, 2014
It’s an exciting yet daunting time to be a security professional. Security threats are becoming more aggressive and voracious. Governments and industry bodies are getting more prescriptive around compliance. Combined with exponentially more complex IT environments, security management is increasingly challenging. Moreover, new “Big Data” technologies purport bringing advanced analytic techniques like predictive analysis and advanced statistical techniques close to the security professional.
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big data, data management, security threats, advanced analytics, security management, predictive analytics, compliance, security, it management
    
EMC Corporation

The Big Data Security Analytics Era is Here

Published By: EMC Corporation     Published Date: Aug 05, 2014
Large organizations can no longer rely on preventive security systems, point security tools, manual processes, and hardened configurations to protect them from targeted attacks and advanced malware. Henceforth, security management must be based upon continuous monitoring and data analysis for up-to-the-minute situational awareness and rapid data-driven security decisions. This means that large organizations have entered the era of data security analytics. Download here to learn more!
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big data, data management, security threats, advanced analytics, security management, predictive analytics, compliance, security
    
EMC Corporation

SBIC Report-Transforming Information Security (Designing a state-of-the-art extended team)

Published By: EMC Corporation     Published Date: Aug 05, 2014
To develop the visibility, agility and speed to deal with advanced threats, traditional security strategies for monitoring, often based around security information and event management (SIEM) systems need to evolve into a central nervous system for large-scale security analytics. In particular, four fundamental capabilites are required: 1. Pervasive visibility 2. Deeper analytics 3. Massive scalability 4. Unified view Download here to learn more!
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big data, data management, security threats, advanced analytics, security management, predictive analytics, compliance, security, business technology
    
EMC Corporation

Information Security is Becoming a Big Data Analytics Problem

Published By: McAfee     Published Date: Feb 06, 2013
Gartner defines "big data analytics" as the practices and technology used to pursue emerging and divergent pattern detection as well as enhance the use of previously disconnected information assets.
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big data analytics, gartner, big data, big security data, advanced targeted attacks, advanced persistent threats, atas, context aware security intelligence, threat intelligence, siem, access control, anti spam, anti spyware, anti virus, application security, auditing, authentication, compliance, disaster recovery, encryption
    
McAfee

From 0 to Know: Real-Time Analytics With SAP HANA

Published By: Advizex     Published Date: Sep 25, 2013
The challenge of Big Data is more than a question of size; it’s about time to insight and action. With the exponential growth of unstructured data such as social media, video and the raw data generated by smartphones and other “intelligent” machines, businesses are buried under an avalanche of data that renders even best-effort analytics slow and sometimes unreliable. As many businesses are learning in this age of Big Data, it’s not just what you know, but when you know it and how much you trust it. Download this white paper and learn that with SAP HANA, companies can react intelligently at the speed of thought to capture new opportunities.
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sap hana, sap, real time analytics, raw data, generation, analytics, big data, business intelligence, trusting big data, insight, action, knowledge management, enterprise applications, data management
    
Advizex

7 Key Considerations for Big Data Adoption

Published By: InfoSys     Published Date: Apr 08, 2013
Big Data: Too Much information, Too Little illumination; As enterprises go about their Big Data adoption journey, there are many pressing questions at hand. What are the Big Data capabilities they desire?
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big data, business intelligence, analytics, data warehousing, infosys
    
InfoSys

Migrating to the Cloud: When Should Your Business Make the Move?

Published By: QTS Data Centers     Published Date: Feb 18, 2014
The cloud has been beneficial to many IT departments by enabling quicker responses to the fast-moving market and ever-changing customer needs. So when is your business migrating over?
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qts, the cloud, migrating, integration, technology, it departments, migration, it leaders, it budget, it budget increase, flexibility, scalability, capital expenditures, service provider, cloud provider, big data, analytics, cloud computing, cloud working, application
    
QTS Data Centers

HP Haven: See the big picture in Big Data - Know your customers better with targeted merchandise

Published By: HP     Published Date: Jan 20, 2015
There are many new ways Big Data analytics can significantly boost marketing and promotional efforts through real-time and historical analysis of online data, such as clickstream or purchase transactions. Unstructured data based on social media—even photos and video—offers enormous potential when analyzed with the right tools.
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big data, hp haven, scalable, secure data platform, ecosystem, security
    
HP

ID1OT Error

Published By: HP     Published Date: Oct 29, 2014
Tired of dealing with ID10T errors? Wouldn't life be easier if you reduced the number of ID10T errors and focused more on the critical issues? HP Service Anywhere seamlessly connects service quality, customer satisfaction and staff efficiency through its easy-to-use social collaborative capabilities. The only service desk with embedded Big Data technology, HP Service Anywhere delivers connected intelligence to IT and business users to support proactive problem solving and actionable analytics.
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itsm, itil, saas help desk, itil service desk, itil service management, itil change management, itil problem management, hp service anywhere, it management, knowledge management, cloud computing
    
HP

Decision Optimization

Published By: FICO     Published Date: Nov 10, 2015
"ACG Michigan, a large auto insurance underwriter in the US state of Michigan, needed a user-friendly system that would enable its agents (internal and independent) to churn out precise and consistent policy quotes and underwriting decisions. They turned to FICO Blaze Advisor decision rules management system to create an enterprise decision management framework to execute decisions. Learn more on how FICO Blaze Advisor helped ACG Michigan automate its underwriting About FICO FICO (NYSE: FICO), formerly known as Fair Isaac, is a leading analytics software company, helping businesses in 90+ countries make better decisions that drive higher levels of growth, profitability and customer satisfaction. The company's groundbreaking use of Big Data and mathematical algorithms to predict consumer behavior has transformed entire industries. FICO provides analytics software and tools used across multiple industries to manage risk, fight fraud, build more profitable customer relationships, optimiz
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decision analytics, optimization, profitability
    
FICO

The Invisible HR Problem

Published By: Infosys     Published Date: May 21, 2018
In HR, working purely on instinct is dangerous. HR Professionals are highly skilled, and their experienced opinion is extremely valuable when it comes to selecting candidates, assessing performance, and all the other important aspects of this function. But can you rely on their instinct alone? This was the big question that our client, a large CPG company was facing. When we realized this was the problem, the solution was obvious. Not necessarily easy, but obvious. There was plenty of data, but it wasn't being used to improve HR decision making. We designed an analytics solution that would improve HR Decision making. We designed an analytics solution that would improve the efficiency of data gathering, to make the HR function more effective. We then proposed an additional layer, which would use artificial intelligence (AI) to improve HR Decision-making further.
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company, employee
    
Infosys

Infosys named a ‘Leader’ in NelsonHall’s Big Data and Analytics NEAT Report 2018

Published By: Infosys     Published Date: Sep 11, 2018
Infosys has been recognized as a ‘Leader’ in NelsonHall’s Vendor Evaluation and Assessment (NEAT) report on big data and analytics services 2018.We have also been highly rated for our focus on automation. Our ability to meet future client requirements as well as deliver immediate benefits such as analytics, data management and support functions to our clients with a specific focus on process automation enabled us to secure this position.
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Infosys

The Definitive Guide to Data Quality

Published By: Talend     Published Date: Nov 02, 2018
Siloed data sources, duplicate entries, data breach risk—how can you scale data quality for ingestion and transformation at big data volumes? Data and analytics capabilities are firmly at the top of CEOs’ investment priorities. Whether you need to make the case for data quality to your c-level or you are responsible for implementing it, the Definitive Guide to Data Quality can help. Download the Definitive Guide to learn how to: Stop bad data before it enters your system Create systems and workflow to manage clean data ingestion and transformation at scale Make the case for the right data quality tools for business insight
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Talend

Smart analytics pay dividends across the customer lifecycle: Read TM Forum Quick Insights Report

Published By: FICO EMEA     Published Date: Jan 25, 2019
Communications service providers (CSPs) have long recognized the potential of data analytics. Yet their early efforts to pull actionable intelligence from the oceans of data they have access to were largely unsuccessful. Many tried a 'big bang' approach to building a central repository without knowing what they wanted to do with the data in it. The arrival of artificial intelligence (AI) – its machine learning subset in particular – has changed their thinking and approach. For this Quick Insights report, we surveyed 64 professionals from CSPs around the world who are applying, leveraging and/ or planning to deploy advanced analytics in some capacity at various points across the customer lifecycle.
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analytics, artificial intelligence, customer lifecycle, insights, telecom credit lifecycle, customer acquisition, optimisation
    
FICO EMEA
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