Getting value from big data starts with the right foundation

Finding real value in data is critical to every business today. But before we mine it for business insights, we need to access this data from all of our relevant sources accurately, securely, and quickly. How? With a foundation that integrates multiple data sources and can transition workloads across on-premise and cloud boundaries.

What is big data?

It's popularly defined by these characteristics, known as the 3 Vs: Massive volumes of data in a variety of nonstandard formats that are processed at a high velocity.

The potential goldmine of big data

Analyzing big data—including often-overlooked dark data—can yield valuable insights that you can use to improve your business. Organizations use these insights to cut costs, operate more efficiently, and find new ways to boost profits. Big data insights can help you prevent costly problems instead of reacting to them, and predict customer behaviors and needs instead of guessing, which can increase revenue.

Numbers don't lie

Clearly the path to optimizing the use of big data is not a simple one. But since we can expect that big data will become even bigger over time, it's a journey that is better started as soon as possible, and with a solid plan in place.

Three ways for CIOs to handle big data, Scott Koegler, The Enterpriser's Project Read the article

Big data use cases

How some successful enterprises are using big data

Big data creates IT challenges

Mining big data is rewarding but complex. Are your data sources reliable? Do you have 1 version of the truth? Do you have adequate storage capacity? Does your hardware-based storage segregate data, making it hard to find, access, and manage? Can your architecture adapt to constantly evolving data technology? Are you taking advantage of the cloud? Is your data protected?

Rethinking data integration [PDF]

In big data, the right foundation makes all the difference

Gaining insights from your data is the end goal. But before you can exploit your big data, you need the right foundation to ensure that the data is comprehensive, reliable, and timely. A foundation that lets you:

  • Easily integrate traditional data-management technologies—like data warehouses and databases—with new ones—like Hadoop and Spark.
  • Adapt to changes in the competitive landscape, emerging technologies, and volatility in the scale of business operations.
  • Prepare for tomorrow while solving your biggest data challenges today.
  • Avoid becoming locked in to any 1 approach or vendor’s stack, because technologies for tackling big data are in the early stages.

If you get your foundation wrong, no amount of investment in analytics software can compensate for it.

5 traits of an effective big data deployment

Building blocks of a successful big data deployment

  • Platform-as-a-service (PaaS)

    Develop apps faster, process data in real time, and easily integrate systems so you can build modular solutions that let your business grow.

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  • Infrastructure-as-a-Service

    Deploy and manage service providers, tools, and components of IT architecture across platforms and technology stacks in a consistent, unified way.

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  • Middleware, integration, and automation

    The need for information and analytics creates new data sources and eventual sprawl—unless you can create a virtualized, single source of data and an easy-to-manage way to connect both internal and external resources. Data processing and other demanding workloads require streamlined interaction and integration.

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  • Storage

    Choose the best storage type per workload with a software-defined, agile storage platform that can integrate file and object storage, Hadoop data services, and in-place analytics.

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How can you get involved?

Hadoop on OpenStack (Project Sahara)

Led by Red Hat and its big data partners, the Sahara project provides a simple means to provision a data-intensive application cluster (Hadoop or Spark) on top of OpenStack.

Get involved

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