Resource Categories: About Cloud Data

Why Technology Businesses Should Migrate To The Data Cloud

Tech businesses are looking to achieve insights and make strategic decisions through the use of superior analytics. The key to performing advanced analytics is a single source of data truth across the organization. But data silos make harnessing the value of data time-consuming and expensive. Governance and collaboration are also often impossible to achieve across different technologies and clouds.

Improving your architecture will help eliminate data silos so you can attain greater business insights and collaborate on data more easily and securely. A modern data architecture also serves a variety of real-time needs for different users and enables a 360-degree customer view.

Many tech businesses are rearchitecting their tech stack on the Snowflake Data Cloud. In this ebook, learn how Snowflake’s technology partners and customers are tapping the flexibility of a cloud-based data platform to help build new products, solutions, and services and improve service delivery.

The Data Warehouse: The Engine that Drives Analytics

How to reinvent your analytics with data warehousing
built for the cloud

What if your organization could easily and affordably implement a solution that gives your business intelligence and data analytics users what they want, when they want?

Our new guide contains the information you’ll need to understand and succeed with modern cloud data warehousing.  It will start you on a path to transform your company’s data analytics with a BONUS cheat sheet on five key topics crucial to getting started with cloud data warehousing:

Learn about:

  • How to analyze vast amounts of varying data with speed
  • How a cloud data warehouse should scale
  • User profiles: Solutions for common demands
  • The big question: What about security?
  • Large-scale physical data transfers – How it’s done
  • TCO and budgeting

TDWI Infographic | BI, Analytics, and the Cloud Best Practices

The cloud is becoming a mature platform for data management, integration, business intelligence (BI), and analytics. Business leaders understand that the cloud can provide flexibility, scalability, and agility for their BI and analytics projects. Instances of the cloud can quickly spin up (or down) without the cost and delays of installing on-premises applications. In the recent TDWI Best Practices Report: BI, Analytics, and the Cloud, we take a look at organizations’ experiences with and plans for cloud BI and analytics, including how satisfied organizations are with the cloud and why, overcoming cloud adoption challenges, and what your organization should consider when moving to the cloud. Here are several of the key survey results.

This infographic explores the results from that report.

TDWI Best Practices Report: BI, Analytics and Cloud Strategies

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Authored by Fern Halper and David Stodder

This report educates organizations in best practices and options for cloud business intelligence (BI) and analytics. This includes organizational strategies for the cloud as well as new platform options and other considerations.

The report also examines how organizations are using cloud BI and analytics and gaining value from them.

Key Findings:

  • Top cloud analytics drivers include scalability, flexibility, and cost
  • Resistance to the cloud is definitely diminishing
  • Organizations should make sure that pricing models are flexible so that they can scale up and down easily

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Please register to review the entire report.

Data Analytics: Beyond the Hype – A Survey by Dimensional Research

This report is based on a survey of 376 individuals with responsibility for data initiatives including 104 executives. The goal of the survey was to understand current experiences, challenges and trends with data analytics initiatives.

Key Findings:

Data initiatives are important, but have serious issues

  • 100% say data analytics is important
  • 48% of executives characterize data analytics as “critically important”
  • 88% have faced “failures” with recent data initiatives

Inflexibility of data infrastructure is the underlying cause of many challenges

  • Data inflexibility tops list of challenges faced by data and analytics
  • 59% of executives say their existing analytics infrastructure is too inflexible
  • 75% of executives are prevented from acting on business requests because their data infrastructure is too inflexible

Cloud-based analytics could help address barriers to data analytics

  • 99% find potential benefits of cloud analytics to be compelling
  • 92% would try more things in a pay-as-you-go model licensing
  • 74% of those that have adopted cloud analytics intend to grow use in the coming year

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Please register to review the entire report.

Eckerson Group’s Product Brief: Snowflake Elastic Data Warehouse

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Product Brief: Snowflake Elastic Data Warehouse

Please register to receive a complimentary copy of Eckerson Group’s Product Brief which provides a summary the innovative technology behind Snowflake’s cloud data warehouse offering.

In this brief, Eckerson Group’s research covers:

-Key differentiators
-Product Profile
-Key Use Cases

Abstract:

“The demand for cloud-based alternatives to traditional data management systems is accelerating rapidly among businesses looking to offload infrastructure and administrative tasks and gain new capabilities that on-premises systems can’t deliver. Snowflake’s Elastic Data Warehouse is a cloud-based data warehousing service that incorporates a flexible data management architecture that decouples storage from compute.”

Register now!

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Where Do I Go from Here?

CIO’s 15th annual State of the CIO study – Special Foreword from Snowflake

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CIO’s 15th annual State of the CIO study – Special foreword from Snowflake Computing

CIO’s 15th annual State of the CIO study finds that IT executives are under intense pressures as they work strategically to digitally transform their businesses and defend company-sensitive information from cyberattacks, all while also trying to build an IT organization that can keep up with the pace of change.

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Check out Snowflake’s exclusive foreword to the 2016 State of the CIO Survey, authored by Jon Bock, VP of Marketing and Products.

Abstract:

“Today, technologies such as the cloud, big data, andanalytics are blurring the lines between IT and business roles—mostly for the good, but not without challenges. The “2016 State of the CIO Survey” reveals the good in those blurred lines: IT executives who have strong relationships with business stakeholders fare better as they deal with the
challenges that accompany digital transformation and all it entails, from cybersecurity to complexity and loss of control.”

Please register to receive the entire report.

Where Do I Go from Here?

Overcoming the reality gap of big data

The ability to access and analyze data is the critical foundational element for competing in new and old industries alike. Yet, a recent survey of IT executives finds that most are still struggling— and frustrated—with widely used data analytics tools.

Survey findings:

Ease of use is top requirement

For data users, far too much time is spent waiting to get access to the data.

Conventional data warehouses were architected for static, predictable workloads, but organizations today are trying to accommodate dynamically changing data and the growing desire for more analytics-based applications and processes.

TDWI Checklist Report: Using and Choosing a Cloud Solution for Data Warehousing

Authored by Colin White

This checklist identifies the benefits the cloud offers, offers potential use cases, and presents key criteria for using and choosing a cloud solution for data warehousing.

Foreward:

The cloud environment offers a pay-as-you-go, on-demand, and elastic scalability model that can provide significant benefits for both the business and IT. Compared to an on-premises IT environment, cloud computing reduces up-front project costs and enables organizations to scale their applications as required while paying only for the resources they use.

The cloud is, therefore, an ideal environment for data warehousing projects given the large data volumes and unpredictable nature of the analytic workloads involved.