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Cisco Partner Weekly Rewind – January 23, 2015

Partner-Weekly-Rewind-v2Each week, we’ll highlight the most important Cisco Partner Ecosystem news and stories, as well as point you to important, Cisco-related partner content you may have missed along the way. Here’s what you might have missed this week:

Off the Top

Great blog this week from Raja Sundaram. He posted Delivering Business Solutions with Connected Analytics and it’s a good look at how Cisco is using its strength in hardware, software, services and partnering to provide powerful analytic solutions.

If you’re interested in how Cisco can partner with you to ensure your data analytics strategy is in place, be sure to check out Raja’s blog as it can provide insight on how:

  • Partners will be able to tap into a high revenue stream as IT services spend, driven by big data, reaches $44B
  • Big data services opportunities supersede hardware and software opportunities, allowing partners to put a premium on these services
  • Partners will be able to wrap business intelligence, analytics, and data management solutions with their capabilities to deliver value-added services that differentiate their practice

Take a look and let us know what else we can relay to you around data analytics. Read More »

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How To Gain an Edge by Taking Data Analytics to the Edge

In Part 1 of this blog series, I talked about how data integration provides a critical foundation for capturing actionable insights that generate improved outcomes. Now, in Part 2, I’ll focus on the two other challenges that must be met to extract value from data: 1) automating the collection of data, and 2) analyzing the data to effectively identify business-relevant, actionable insights. This is where things, data, processes, and people come together.

Let’s start with automation.

After IoT data is captured and integrated, organizations must get the data to the right place at the right time (and to the right people) so it can be analyzed. This includes automatically assessing the data to determine whether it needs to be moved to the “center” (a data center or the cloud) or analyzed where it is, at the “edge” of the network (“moving the analytics to the data”). Analytics at the Edge

The edge of the network is essentially the place where data is captured. On the other hand, the “center” of the network refers to offsite locations such as the cloud and remote data centers — places where data is transmitted for offsite storage and processing, usually for traditional reporting purposes. The edge effectively could be anywhere, such as on a manufacturing plant floor, in a retail store, or on a moving vehicle.

In “edge computing,” therefore, applications, data, and services are pushed to the logical extremes of a network — away from the center — to enable analytics knowledge generation and immediate decision-making at the source of the data.

Read More »

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Why Data Integration Provides the Critical Foundation for Capturing Actionable Insights

We all know that Big Data is getting bigger. And, the gap between the amount of data with hidden value and the amount of value that is actually extracted keeps widening. In fact, according to IDC, less than 1 percent of the world’s data is currently being analyzed. What good is data if it doesn’t produce actionable insights that generate improved outcomes?

A large portion of the world’s data is produced by the billions of connected objects that make up the Internet of Things (IoT), a critical enabler of the Internet of Everything. In Cisco Consulting Services, we recently conducted a blind global survey to learn more about how organizations are harnessing IoT to transform their businesses — and what they can do to drive more value. Read More »

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IoT: Moving from Connecting Devices to Capturing Insights

There’s a lot at stake—$19 trillion in fact—as companies transform into digital businesses to capture value from the Internet of Everything (IoE). More than 42 percent of this value, or $8 trillion, will come from one of IoE’s chief enablers, the Internet of Things (IoT). While IoE is the networked connection of people, process, data, and things, IoT is the intelligent connectivity of physical devices that is driving massive gains in efficiency, business growth, and quality of life. So why worry about IoT when we have IoE? Simple, IoT often represents the quickest path to IoE and the $19 trillion that’s there for the taking.

Cisco Consulting Services recently conducted a blind global survey to Read More »

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Transparently Offloading Data Warehouse Data to Hadoop using Data Virtualization

More data allows for better and more expansive analysis. And better analysis is a critical success factor for businesses today.

But most data warehouses use the once-in-never-out principle when storing data. So whenever new business activities occur, new data is added without removing old data to make room. New data sources, such as data from social media networks, open data sources, and public web services further expand the warehouse. Unfortunately, all this growth comes at a cost.

Is there a way you can have your cake and eat it too?

With Hadoop and Cisco Big Data Warehouse Expansion, you can.

Disadvantages of More Data

While everyone understands the business advantage that can be derived from analyzing more data, not everyone understands the disadvantages that can occur including:

  • Expensive data storage: Data warehouse costs include hardware costs, management costs, and database server license fees.  These grow in line with scale.
  • Poor query performance: The bigger the database tables, the slower the queries.
  • Poor loading performance: As tables grow, loading new data also slows down.
  • Slow backup/recovery: The larger the database, the longer the backup and restore process.
  • Expensive database administration: Larger databases require more database administration including tuning and optimizing the database server, the tables, the buffer, and so on.

Three Options to Control Costs

The easiest way to control data warehouse costs is to simply remove data, especially the less-frequently used or older data. But then this data can no longer be analyzed.

Another option is to move the lesser-used data to tape. This option provides cost savings, and in an emergency, the data can be reloaded from tape. But analysis has now become EXTREMELY difficult.

The third option is to offload lesser-used data to cheaper online data storage, with Hadoop the obvious choice. This provides a 10x cost savings over traditional databases, while retaining the online access required for analysis.

This is the “have your cake and eat it too” option.

The Fast Path to Transparent Offloading

Cisco provides a packaged solution called Cisco Big Data Warehouse Expansion, which includes the data virtualization software, hardware, and services required to accelerate all the activities involved in offloading data from a data warehouse to Hadoop.

And to help you understand how it works, Rick van der Lans, data virtualization’s leading independent analyst, recently wrote a step-by-step white paper, Transparently Offloading Data Warehouse Data to Hadoop using Data Virtualization, that explains everything you need to do.

Read The White Paper

Download Transparently Offloading Data Warehouse Data to Hadoop using Data Virtualization here.

 

Learn More

To learn more about Cisco Data Virtualization, check out our page.

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