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Kelle O'Neal

Thanks for joining our data conversation! This blog is an opportunity to share the real life challenges, opportunities and approaches to improving the quality and value of data in your organization. We will write about everything data related from translating "data" speak into "business" speak, to governance models, to the real differences among the myriad software tools available. But there's one catch: we all have to agree to toss out the fluff. That's right, no 30,000 foot, theoretical strategies that leave you wondering how to execute and actually improve performance. Visit regularly to learn from peers and partners on how they are managing and improving data, and we hope you'll also share your views and experiences.

About the author >

As Founder and Managing Partner of First San Francisco Partners, Kelle O’Neal manages specialist data governance and data management consulting services to complex organizations that deliver faster time to results. Kelle can be reached at kelle@firstsanfranciscopartners.com or through the First San Francisco Partners website.

Follow First San Francisco Partners on Twitter at @1stSanFrancsico.

Editor's Note: Find more articles and resources in Kelle's BeyeNETWORK Expert Channel. Be sure to visit today!


September 2012 Archives

The amount of data companies are faced with today is daunting. Companies are struggling to deal with greater data volumes as well as increased data complexity. Wikipedia states that, "2.5 quintillion bytes of data are created on a daily basis and 90% of the data in the world today was created within the past two years." The amount of data will continue to grow exponentially for the foreseeable future. Massive data volumes and complexity are here to stay.

So, what exactly is Big Data? We define big data as extremely large data--in terms of volumes and sizes--from nontraditional data sources that cannot easily be captured, processed, analyzed, shared, stored, and managed using traditional technology, analytical tools and resources. Big data includes the proliferation of data streaming in from mobile devices, gathered from social media, and generated from images, video, etc. Big data can be structured, unstructured or multi-structured.

While big data is presenting new business opportunities, it is also exposing IT challenges. If properly managed, secured and used, big data provides opportunities to uncover valuable insights about customer needs and their satisfaction levels, leads to improved product innovation and makes your business more agile.

Yet, before big data can add value to an organization, it needs to be captured, processed and analyzed, and integrated with other enterprise data. The process of integrating and managing big data and its relationships across the enterprise is referred to as Big Data Management (BDM). BDM defines the policies, processes, people and technology that help companies to integrate and use big data throughout an organization. The ultimate goal is to find insights in the data so an organization can make decisions based on facts rather than instinct and thus become more nimble and decisive. BDM also helps answer business questions that are more predictive in nature. In many companies, such answers were previously considered unattainable.

There are four characteristics that define big data:

  • Volume - The amount and extent of the data

  • Velocity - The speed of the data received and sent

  • Variety - The different data types and external sources of the data

  • Value - The business insights the data provides

  • How big does a data set have to be to be considered big data? The size of big data varies depending on the maturity of an organization. Present parameters are on the order of terabytes, petabytes, exabytes, zettabytes, etc. For some organizations, having gigabytes of data may qualify as big data; for others, it may take terabytes of data for data to be considered big data.

    Big data comes from a variety of sources. Social media data comes from blogs, Facebook, Twitter, LinkedIn, etc. Sensor data from radio frequency identification (RFID) chips/readers, wireless sensor networks, etc. creates streams of data about usage. Log data keeps track of everyone who registers or checks into a web site, what pages they visit, when they are there, etc. This type of data comes from software logs, web logs and server log files. Device data can come from mobile devices, GPSs, appliances that call home, and healthcare devices used by at-home patients. Big data can also come from audio, images, video, emails, documents, etc. No wonder big data is growing exponentially!

    But organizations have been wrestling with data for a long time. How is big data different from data that is already inside the enterprise? The table below shows key differences according to the characteristics of big data defined above. In the table, "Small Data" refers to data that already exists inside the enterprise.

    Big data Small data v4.png We believe that when big data is integrated with other enterprise data organizations can develop a more insightful understanding of their business. This can lead to better product innovation, business model advances and streamlined business processes. These improvements, in turn, can lead to a stronger competitive edge, and increased revenue and growth. The changes that big data are bringing about are at a tipping point and are set to grow significantly. It's important to your business and that's why everyone is talking about it.

    How do you define Big Data?

    Check back in for more on this topic.



    Posted September 17, 2012 4:28 PM
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