Big Data & Analytics The DNA to a Successful Implementation in 2016

In the past five years, Big Data has truly gained momentum. 2015 was the year companies started to invest in Big Data Analytics strategy aggressively, moving beyond the challenge of simply ‘getting data in’ and focusing on the basics of both good infrastructure and sound security. The companies that addressed infrastructure and security in 2015 are now in a great place to explore new ways of protecting their market share. In 2016, they are putting solutions in place to get a 360-degree view of all their data channels to improve management of their networks and services, and even more importantly, they are part of the massive drive for real-time Big Data.

Spotlight

Pivotal

Pivotal’s cloud native platform drives software innovation for many of the world’s most admired brands. With millions of developers in communities around the world, Pivotal technology touches billions of users every day. After shaping the software development culture of Silicon Valley's most valuable companies for over a decade, today Pivotal leads a global technology movement transforming how the world builds software.

OTHER WHITEPAPERS
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Increase Agility and Reduce Costs with a Logical Data Warehouse

whitePaper |

A Logical Data Warehouse solves the problem of consolidating critical data scattered across silos, providing a comprehensive, actionable view of data assets. Coined by Gartner, the “Logical Data Warehouse” is also referred to as ‘data virtualization,’ ‘data layer,’ ‘data cloud,’ ‘data lake’, ‘data fabric’, and many other terms depending on the industry and environment.

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Advanced Analytics with Spark: Patterns for Learning from Data at Scale

whitePaper |

Build a model to detect credit card fraud using thousands of features and billions of transactions. Intelligently recommend millions of products to millions of users. Estimate financial risk through simulations of portfolios including millions of instruments. Easily manipulate data from thousands of human genomes to detect genetic associations with disease. These are tasks that simply could not be accomplished 5 or 10 years ago. When people say that we live in an age of “big data,” they mean that we have tools for collecting, storing, and processing information at a scale previously unheard of. Sitting behind these capabilities is an ecosystem of open source software that can leverage clusters of commodity computers to chug through massive amounts of data.

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Enterprise in Big Data

whitePaper |

Today the term big data draws a lot of attention, but behind the hype there's a simple story. For decades, companies have been making business decisions based on transactional data stored in relational databases. Beyond that critical data, however, is a potential treasure trove of non-traditional, less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Decreases in the cost of both storage and compute power have made it feasible to collect this data - which would have been thrown away only a few years ago. As a result, more and more companies are looking to include non-traditional yet potentially very valuable data with their traditional enterprise data in their business intelligence analysis.

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The IRA, Social Media and Political Polarization in the United States, 2012-2018 (Appendices)

whitePaper | November 8, 2018

This section presents the monthly timelines of Facebook and Instagram organic posts, in Figures 1 and 2. Figure 1 shows that monthly Facebook post volume picks up again from July to August 2017, as noted in the main report. It also shows very low activity till June 2015, and an increase in activity from that point onwards, which rises steeply from September to October 2016 (months immediately prior to the election in November 2016). In addition, it shows that post volume is very high in 2017, generally higher than 2016 and 2015 levels, and remains high even after the drop in summer 2017.

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Big Data, Big Needs

whitePaper |

The need for data-fluent talent has become one of the definitive jobs issues in our country and globally, and touches all levels across all industries. Unlocking the power of data has the potential to drive tremendous growth for our economy, and the explosion of business-related data reveals a growing need for talent that can capitalize on the opportunities buried in the numbers. This paper explores this pervasive skills gap and the partnerships between corporate America and post-secondary education required to address the gap, based on discussions held during the “Big Data/Open Data: Inspiring Corporate & Civic Innovation” conference held March, 2016 featuring over 20 experts from Fortune 500 business, higher education and government, and hosted by University of Phoenix.

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Accelerating Data Modernization with Azure

whitePaper | May 18, 2021

Next-gen data operations require next-gen data technologies and strategies and Azure is an ideal platform for this modernization to take place. Download this white paper to better understand the strategies, philosophies, and technologies your organization needs to expand analytics abilities, reduce technical debt, embrace AI, and more.

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Spotlight

Pivotal

Pivotal’s cloud native platform drives software innovation for many of the world’s most admired brands. With millions of developers in communities around the world, Pivotal technology touches billions of users every day. After shaping the software development culture of Silicon Valley's most valuable companies for over a decade, today Pivotal leads a global technology movement transforming how the world builds software.

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