#implementation of big data

Big data has become an exploding area of discussion, implementation, opportunity and reward for many companies. I present today some key steps in the phase and journey of your big data implementation.

Key elements of this article:

1)      Identification of each critical big data implementation phase

2)      Key points within each phase for metric measurement

3)      Business skills, strategy and technology phases

4)      What may be beyond big data?

First Steps (The new arrival)

This is the awareness generation phase of the business and its management and leaders. At this phase there will be the information gathering from media, conferences, suppliers, competitors and customers. Although it is able to pivot progress through out each step of the big data journey, the lessons learnt at this early phase is worth spending a little more time. The return will be potential strategy direction, speed of implementation and clarity of resources required.

There may be the initial pilot test case experience from within the industry or within the companies own trial. Creating a “lessons learned” phase of review is encouraged so fine tuning can be made.

 I suggest a good starting point to be “Big Data” by Bernard Marr for both generating awareness and creating some basic guidelines for your pilot project. My personal opinion is Bernard’s book generates a fair framework but does not concentrate enough on some key elements: Data Security, Privacy and Future Regulation direction, alignment between the values from the culture generating the data sets and the values of the business collecting it.

New technology and strategy considerations to Big Data opportunities start to be made aware and considered within the business from software purchase, system design and data quality standards.

Geeking Out (Early Teens)

This is phase where business has embraced the idea and concept of big data. The CEO and leadership accept a vision for their business needs. Ironically I often see that the responsibility is often shifted over to the CIO and IT department almost exclusively. The IT “get it” and so who better in the business to lead big data implementation?

Pilot schemes and some “proof” through success stories are generated by the IT department to  wet the appetite further within management and the business culture. Investment and basic use of analytics is implemented with moderate and variable success.

In the meantime, the business goes all out to collect as much big data relevant information but is generally stored “waiting” for full implementation and the development of a new project or strategy phase.

This phase causes some tantrums in the business for budget level and resource priorities, the gains are mostly in the IT silo.

Taking things serious (Early Twenties)

A company that has progressed to this phase of its journey within big data implementation is investing the correct resources and expertise. The business will likely be engaged at some levels with regular analysis. The analysis structure may or may not be generating significant value to the participants. Communication to understand the needs of the business is important to avoid unstructured analysis and thus affect the efficiency and effectiveness of big data as it starts to roll out and cascade into various areas of the business.

Skill levels at this point become more critical, and the appointment of a good data scientist is deemed as a necessity.

The use of predictive analytics with data gathered so far makes an entry point to the company and helps identify some final steps of clarify to the operating framework of big data within the business operations.

Integrated business (Nest building)

Well done if your business has got this far! This phase is currently more a lonely lane of traffic than traffic jammed highway in the big data environment. The company is engaged and committed to including big data as an integral part to its operations. By this phase your skills across the business is becoming stronger for successful project implementations and common agreement is made surrounding vital elements of the big data architecture.

A big data policy is created and rolls out as standard practice and reference within the business. This affects the skills, metrics, purchases, market interactions and deeper crossover and integration of data best practices. Quality of data and clarity of specific desired data sets is managed and rolled through the company whilst drawing and setting requirements on the company external contact points of interaction. These generate informational metadata standards for the business.

Management confidence and reliability of the data sources accuracy provides analytical tools the birth and power of predictive insights integrated within business operations. This has the potential to define new profit and cost areas for attention and action. At this point big data is creating good value for the business.

The Serviced Industry (The golden years)

If the prior phase of implementation of the big data journey is less traveled in current markets then the golden year’s phase of implementation is the current “el dorado” of big data implementation. It is worthy to note that this phase will become a rapidly filled over the next few years. The explosion of project, resources and solutions is encouraging.

The golden years will be filled with true self service and on demand data delights. The complexity of developed algorithms will allow most people within the business to explore potential directions and instant improvements. The strong and smart will become the clear winners of this arena!

Big data will no longer be seen as a quest but simply part of the functions, structure and back bone of business by being a data service provider.

The scenarios generated through predictive analytics will offer new collaboration arenas between departments, suppliers, and markets alike. An open sharing of analytics will spread across the whole market and business enterprise.

Who knows? (Is there life after Big Data?)

So far much debate and direction takes us to the golden year’s phase of big data implementation. We see the potential of virtual reality, machine learning and artificial intelligence gathering pace and momentum. These key areas will no doubt effect the direction and journey of big data, but where it will take us beyond and into the future is anyone’s guess. We know today that Asimov and Orwell under estimated many areas of technology development and I suggest this is the case with today’s current science fiction. It seems even our imagination is the limit!

Performance Direction and Impacts:

The clear phase steps above, allows a business to embrace the strategic steps to measure its progress and performance in the implementation of big data. Your business can take these steps as clear milestones and using the details within as metric guidelines to progress and challenges to be overcome. The impacts are clear and understandable at all levels of the business.

What phase of big data implementation are you currently working within? Do you recognize these steps in your own business? I am keen to hear your experiences and JAMSO is willing to help clarify and support your business in its big data journey.

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Further Reading and Reference:

Metadata

Big Data Trends in 2015

JAMSO Pins on Pinterest on Big data and business intelligence

Analytics Magazine white papers