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Published By: KPMG     Published Date: Jun 10, 2019
Getting complex decisions right across complicated operational networks is the key to optimum performance. Find out how one of the UK’s biggest bus operators is using data and analytics to make better decisions and optimise the use of resources across their network. Read this story to discover: • how data and analytics can transform operational performance • the benefits of using decision-support tools in the middle office • key lessons for getting your plans for digital transformation right.
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KPMG
Published By: NTT Ltd.     Published Date: Jan 16, 2019
NTT Data services has over 600+ BI experts and over 250+ implementations in India, receiving high accolades from Gartner and AMR research. NTT Data Services offers Industry focused offerings and pre-configured models. Some of our offerings include: - Guided Analytics Strategy - Proven Framework & Methodology for ‘C’ level executives - Solution lab for Co-Innovation and Proof of Concepts - Advisory Services - BI Transformations, Big Data Strategy, Information Governance, Health Checks - Proprietary Tools & Accelerators – System Optimization, Architect to Archive, User Adoption - Flexible Delivery - Rapid Development Factory, Shared Services Find more details in this deck.
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NTT Ltd.
Published By: BMC ASEAN     Published Date: Dec 18, 2018
Digital transformation encompasses both technological and human components. While many initiatives focus on ensuring that a company’s multi-cloud infrastructure is agile enough to meet changing demands around cloud mobile, Internet of Things (IoT), and big data, it’s equally important to empower business workers with the modern digital tools they need to be successful today. Artificial intelligence and machine learning can play a vital role on both of these fronts. In fact, 78 percent of CIOs and senior IT leaders are already looking to AI to address complexity,1 and by 2019, 30 percent of IT service desks will utilize machine learning to free up support capacity.2 The magnitude of change has forced companies to take stock of the experience they offer employees. As digital natives3 enter and advance in the workforce, talent retention is now a top priority. These workers expect to have the best tools; 93 percent of millennials cited modern and up-to-date technology as one of the most
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BMC ASEAN
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
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
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
Published By: Splunk     Published Date: Aug 21, 2018
SIEM (security information and event management) software offers a lot of promise, but legacy SIEMs simply can't keep up with the rate and sophistication of today's cyberattacks. Organizations today require access to analytics-driven SIEMs that combine a big data platform that is optimized for machine data with advanced analytics, threat detection, monitoring tools, incident response tools and multiple forms of threat intelligence. Download your complimentary copy of “The Six Essential Capabilities of an Analytics-Driven SIEM” and learn how to dramatically improve your security posture, advanced threat detection and incident response.
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Splunk
Published By: TIBCO Software     Published Date: Aug 15, 2018
TIBCO Spotfire® Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms. Spotfire Data Science provides a complete array of tools (from visual workflows to Python notebooks) for the data scientist to work with data of any magnitude, and it connects natively to most sources of data, including Apache™ Hadoop®, Spark®, Hive®, and relational databases. While providing security and governance, the advanced analytic platform allows the analytics team to share and deploy predictive analytics and machine learning insights with the rest of the organization, white providing security and governance, driving action for the business.
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TIBCO Software
Published By: Hitachi Vantara     Published Date: Aug 14, 2018
In this book, we are going to look at the key trends driving the modernization of data infrastructure. We’ll see how organizations are adapting and flourishing in a data-driven world. For some time, headlines have been around the internet of things (IoT), big data and data analytics. While these developments are important, the reality is that you cannot take full advantage of them without modernization. We’re going to look at these trends and priorities in detail, then look at the three key drivers of modernization: governance, mobilization and analytics. We’ll also consider the technologies that make up modern data infrastructure including artificial intelligence (AI), flash storage, converged and hyperconverged platforms and software-defined infrastructures. By making sense of data, we make sense of the world. With more data than ever before, we have the tools to turn all that information into intelligent innovation and change the way the world works.
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data infrastructure, big data, internet of things
    
Hitachi Vantara
Published By: AWS - ROI DNA     Published Date: Aug 09, 2018
In today's big data digital world, your organization produces large volumes of data with great velocity. Generating value from this data and guiding decision making require quick capture, analysis and action. Without strategies to turn data into insights, the data loses its value and insights become irrelevant. Real-time data inegration and analytics tools play a crucial role in harnessing your data so you can enable business and IT stakeholders to make evidence-based decisions
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AWS - ROI DNA
Published By: Hitachi Vantara     Published Date: Aug 02, 2018
In this book, we are going to look at the key trends driving the modernization of data infrastructure. We’ll see how organizations are adapting and flourishing in a data-driven world. For some time, headlines have been around the internet of things (IoT), big data and data analytics. While these developments are important, the reality is that you cannot take full advantage of them without modernization. We’re going to look at these trends and priorities in detail, then look at the three key drivers of modernization: governance, mobilization and analytics. We’ll also consider the technologies that make up modern data infrastructure including artificial intelligence (AI), flash storage, converged and hyperconverged platforms and software-defined infrastructures. By making sense of data, we make sense of the world. With more data than ever before, we have the tools to turn all that information into intelligent innovation and change the way the world works.
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data infrastructure, big data, internet of things
    
Hitachi Vantara
Published By: Amazon Web Services     Published Date: Jul 25, 2018
Organizations are collecting and analyzing increasing amounts of data making it difficult for traditional on-premises solutions for data storage, data management, and analytics to keep pace. Amazon S3 and Amazon Glacier provide an ideal storage solution for data lakes. They provide options such as a breadth and depth of integration with traditional big data analytics tools as well as innovative query-in-place analytics tools that help you eliminate costly and complex extract, transform, and load processes. This guide explains each of these options and provides best practices for building your Amazon S3-based data lake.
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Amazon Web Services
Published By: Pindrop Security     Published Date: Apr 26, 2018
As fraudsters grow in sophistication and experience, they often aren’t acting alone. Syndicated crime rings are big business around the world. In the fraud economy, different fraudsters specialize in different aspects of the attack, from gathering data and creating profiles of targeted victims, to socially engineering call center agents, to creating tools like robotic dialers. These fraudsters might work alone, selling their skills on the black market. In other cases, fraudsters are running entire call centers overseas dedicated to executing attacks.
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Pindrop Security
Published By: Pindrop Security     Published Date: Apr 26, 2018
As fraudsters grow in sophistication and experience, they often aren’t acting alone. Syndicated crime rings are big business around the world. In the fraud economy, different fraudsters specialize in different aspects of the attack, from gathering data and creating profiles of targeted victims, to socially engineering call center agents, to creating tools like robotic dialers. These fraudsters might work alone, selling their skills on the black market. In other cases, fraudsters are running entire call centers overseas dedicated to executing attacks.
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Pindrop Security
Published By: Pindrop Security     Published Date: Mar 21, 2018
As fraudsters grow in sophistication and experience, they often aren’t acting alone. Syndicated crime rings are big business around the world. In the fraud economy, different fraudsters specialize in different aspects of the attack, from gathering data and creating profiles of targeted victims, to socially engineering call center agents, to creating tools like robotic dialers. These fraudsters might work alone, selling their skills on the black market. In other cases, fraudsters are running entire call centers overseas dedicated to executing attacks.
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Pindrop Security
Published By: FICO     Published Date: Dec 04, 2017
In an era where Big Data decisions demand high-powered tools, organizations everywhere are still mired in complex spreadsheets that limit the speed and precision of their critical customer interactions. Read this fact sheet to learn how you can evolve beyond what spreadsheets alone can achieve: • Allow business users to easily create and compare “what if” scenarios, interact with compelling visualizations, and challenge, improve and build trust with stakeholders and collaborators • Rapidly deploy new optimization features and applications practically at the speed of thought – without leaning on IT – while leveraging existing investments in other analytic tools (such as R, SAS, MATLAB, and even Excel) Download Now
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fico, optimization, modeler, industry, analytic, tool, business, solutions
    
FICO
Published By: IBM Watson Health     Published Date: Nov 10, 2017
To address the volume, velocity, and variety of data necessary for population health management, healthcare organizations need a big data solution that can integrate with other technologies to optimize care management, care coordination, risk identification and stratification and patient engagement. Read this whitepaper and discover how to build a data infrastructure using the right combination of data sources, a “data lake” framework with massively parallel computing that expedites the answering of queries and the generation of reports to support care teams, analytic tools that identify care gaps and rising risk, predictive modeling, and effective screening mechanisms that quickly find relevant data. In addition to learning about these crucial tools for making your organization’s data infrastructure robust, scalable, and flexible, get valuable information about big data developments such as natural language processing and geographical information systems. Such tools can provide insig
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population health management, big data, data, data analytics, big data solution, data infrastructure, analytic tools, predictive modeling
    
IBM Watson Health
Published By: Oracle Analytics     Published Date: Oct 06, 2017
Empowered with mobile and cloud-based access to a myriad of products and services, customers now have a variety of options at their fingertips with regards to partnerships. Enterprises that do not follow the ever-changing tastes and preferences of their customers, or that wait too long to react, will fall behind and fail. Across functions, business professionals readily require big data tools and insights to understand and serve these customers. It is no longer an option for business users to rely on IT to deliver customer and other relevant analytics. On the flipside, handing the analytics reins entirely to business users can make governance nearly impossible. Organizations must find balance in a new approach in which IT mostly governs and curates data while business users are empowered to derive insights from data mostly ontheir own without delay.
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Oracle Analytics
Published By: Carbonite     Published Date: Oct 05, 2017
Not long ago, the biggest concern for IT decision makers considering moving workloads to the cloud was security. That’s no longer the case. Today, the main obstacle to cloud adoption is different but familiar: the pain of migrating data. Traditional data migration causes major headaches: • Hours or days of downtime while servers replicate and stakeholders verify functionality • Data loss and migration failures due to inadequate tools and inability to test • Key internal resources diverted from strategic initiatives
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data migration, cloud security, carbonite, data security, cloud platform, cloud adoption
    
Carbonite
Published By: IBM     Published Date: Apr 18, 2017
The data integration tool market was worth approximately $2.8 billion in constant currency at the end of 2015, an increase of 10.5% from the end of 2014. The discipline of data integration comprises the practices, architectural techniques and tools that ingest, transform, combine and provision data across the spectrum of information types in the enterprise and beyond — to meet the data consumption requirements of all applications and business processes. The biggest changes in the market from 2015 are the increased demand for data virtualization, the growing use of data integration tools to combine "data lakes" with existing integration solutions, and the overall expectation that data integration will become cloud- and on-premises-agnostic.
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data integration, data security, data optimization, data virtualization, database security, data analytics, data innovation
    
IBM
Published By: IBM     Published Date: Apr 14, 2017
Any organization wishing to process big data from newly identified data sources, needs to first determine the characteristics of the data and then define the requirements that need to be met to be able to ingest, profile, clean,transform and integrate this data to ready it for analysis. Having done that, it may well be the case that existing tools may not cater for the data variety, data volume and data velocity that these new data sources bring. If this occurs then clearly new technology will need to be considered to meet the needs of the business going forward.
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data integration, big data, data sources, business needs, technological advancements, scaling data
    
IBM
Published By: Waterline Data & Research Partners     Published Date: Nov 07, 2016
Today, businesses pour Big Data into data lakes to help them answer the big questions: Which product to take to market? How to reduce fraud? How to retain more customers? People need to get these answers faster than ever before to reduce “time to answer” from months to minutes. The data is coming in fast and the answers must come just as fast. The answer is self-service data preparation and analytics tools, but with that comes an expectation that the right data is going to be there. Only by using a data catalog can you find the right data quickly to get the expected insight and business value. Download this white paper to learn more!
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Waterline Data & Research Partners
Published By: Cisco     Published Date: Jun 21, 2016
Enterprises are leveraging advancements in what IDC calls “3rd Platform” technologies — cloud, Big Data, mobility, and social — to create new business opportunities and gain competitive advantage. These trends are putting more pressure on IT organizations to transform their datacenter operations to better support business initiatives aimed at reducing costs, increasing revenue, and strengthening customer relationships. This has driven increased demand for converged or integrated systems that provide the tools needed to reduce capital costs, improve operational efficiencies and, ultimately, increase agility within the datacenter.
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Cisco
Published By: Cisco     Published Date: Jun 21, 2016
Enterprises are leveraging advancements in what IDC calls “3rd Platform” technologies — cloud, Big Data, mobility, and social — to create new business opportunities and gain competitive advantage. These trends are putting more pressure on IT organizations to transform their datacenter operations to better support business initiatives aimed at reducing costs, increasing revenue, and strengthening customer relationships. This has driven increased demand for converged or integrated systems that provide the tools needed to reduce capital costs, improve operational efficiencies and, ultimately, increase agility within the datacenter.
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Cisco
Published By: FICO     Published Date: Jun 07, 2016
With the increasing mainstream adoption of big data infrastructure — highly distributed file storage and query tools — more businesses are taking a new look at what business intelligence and analytics can do to grow revenue, increase profits and ultimately develop strategic relationships with customers.
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FICO
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