Big Data, Agile, CIO - 2012 in Review

Speaking on Big Data in 2012
 For my last post of 2012, I thought I'd review some of the major themes that I covered this year.

I completed several posts on Big Data's organizational challenges. Big Data is a significant opportunity for CIOs and IT Leaders because of its managerial challenges and talent/organizational opportunities. For the CIO, the data largely often exists in multiple repositories and there are technology challenges managing the volume, velocity, and variety of data, but the bigger challenges lie in analytics, exposing the truth, and getting the business to act more data driven. I posted three ways data scientists can differentiate and suggested that spreadsheet jockeys needed to retool to stay relevant - posts to help data junkies see beyond their number crunching activities. For those wanting to read about architecture or technology, I posted my top five tools for big data analytics. In my most recent post, I answer the question of what really is big data. Look for more posts in 2013.

I'm still a big agile in the enterprise advocate and in 2012, followed up my many posts on agile development and agile planning with two highly strategic posts. My strategic agile thinking post is a tool I use to get engineers and product owners to prioritize and think about business value, innovation, technical complexity, and architecture. A personal favorite post is on how and why to estimate in agile where I document the specific process I've used in several companies to develop and leverage estimates to make decisions on what to build, and what not to build.

I also wrote a number of posts for CIOs and IT leaders from the art of listening and answering questions to developing executive level presentations. My more detailed posts covered topics on visiting offshore teams, learning from startups, my tweets from this year's Gartner symposium, and on the CIO Paradox.

What can you expect in 2013? A little more of what you see on Big Data, Agile, and CIOs plus more. I will start a new theme covering innovation in the enterprise. Thanks for reading and tweeting!




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What Is Big Data? The Real Challenges Beyond Volume, Velocity and Variety

Big Data's Challenges
I was asked this week by a colleague, "What is your definition of Big Data"? Here's how I responded.

The technology industry describes Big Data in technology terms such as Volume, Velocity and Variety of data or too much data to store and process in traditional data warehouse infrastructure. This might help make technologists aware of the challenges in data management around large, changing, and unstructured data sets. It helps technology vendors sell new capabilities to address these challenges, the media to rally CIOs to invest in them and build awareness around the challenges attracting talent to analyze them.

But that's not a good business definition of Big Data.

Big Data for All Businesses

Every enterprise already collects lots of data, but under utilizes it for intelligence, insight, and decision making. Data exists in disparate databases that can't easily be connected and analyzed holistically. Unstructured data in the form of documents, spreadsheets and presentations exist that are largely used for individual or departmental needs and rarely coalesced and analyzed. Enterprises that have deployed collaboration platforms have the opportunity to better leverage the networks and intelligence of its employees by analyzing relationships, contributions, and consumption on these platforms. Data collected in workflow solutions such as ERP and CRM are rarely merged and analyzed for intelligence. Email is certainly one of the largest repositories of unstructured data.

Bottom line is, all enterprises already have big data. By my definition, Big Data is not defined by its data management challenges, but by the organization's capabilities in analyzing the data, deriving intelligence from it, and leveraging it to make forward looking decisions. It should also be defined by the organization's capability in creating new data streams and aggregating them into its data warehouses.

Volume, variety, and velocity of data define the overall size and complexity of Big Data's data management challenges and for some, the size requires a different architecture than traditional data warehouses. But the real Big Data challenge, and the challenge for all business regardless of size or complexity is in transforming to a data driven organization driven by analysis and insight of existing and new data streams.

See my previous posts on this subject including Big Data, Big CIO Opportunity, Big Data Needs to Scale, Big Data's Managerial Challenges, and my Top Five Tools of Big Data Analytics.
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About Isaac Sacolick

Isaac Sacolick is President of StarCIO, a technology leadership company that guides organizations on building digital transformation core competencies. He is the author of Digital Trailblazer and the Amazon bestseller Driving Digital and speaks about agile planning, devops, data science, product management, and other digital transformation best practices. Sacolick is a recognized top social CIO, a digital transformation influencer, and has over 900 articles published at InfoWorld, CIO.com, his blog Social, Agile, and Transformation, and other sites. You can find him sharing new insights @NYIke on Twitter, his Driving Digital Standup YouTube channel, or during the Coffee with Digital Trailblazers.