July Insights On Big Data & Business Transformation

It’s been a busy month in Big Data, and we’ve been deep in learning about what factors are driving the industry. We’ve translated our experience, research and insight into five key lessons.

Here’s what we’ve learnt this month.

 

#1 – PLAN & TEST FIRST, INTEGRATE LATER

“Big data has proven to be a valuable business asset, but using it to gain competitive advantage requires the right combination of strategy, technology and execution.” – Mahmood Majeed: Managing Partner at ZS Associates.

In all the excitement of implementing a Big Data strategy, It’s easy to get caught up in the hype of new technologies promising to do magical things with your data, and make hasty decisions that once integrated, can be disappointing.

To avoid this, team leaders of Big Data projects must ensure that expectations and output are aligned.

“Start by developing a strategy across the entire enterprise that includes a clear understanding of what you hope to accomplish and how success will be measured.” – Harvard Business Review.

 

#2 – SECURITY IS NOT AN AFTERTHOUGHT, IT’S A NECESSITY

“Big Data and analytics is showing promise with improving cyber security. 90% of respondents from MeriTalk’s new U.S. government survey said they’ve seen a decline in security breaches.” – SentinelOne.

With the volume of worldwide data reaching unprecedented levels, new cyber security threats are emerging daily. To combat this, an article in CSO discusses the benefits of using historical data to identify potential cyber attacks while also predicting future events.

“Using this historical data, you can create statistical baselines to identify what is ‘normal’. You will then be able to determine when the data deviates from the norm.This historical data can also create new possibilities for predictive models, statistical models, and machine learning.”

 

#3 – IT’S ABOUT QUALITY, NOT VOLUME

“Because Big Data presents new features, its data quality also faces many challenges.” – Li Cai & Yangyong Zhu: Fudan University.

As data evolves, new challenges emerge which is why it’s important for businesses to develop data quality standards. With the rise of insight-driven business models, the quality of the data used is key to making the right decisions. Leaders of Big Data projects must ensure that the data is accurate for the intended use.

“Data quality depends not only on its own features, but also on the business environment using the data, including business processes and business users.” – Data Science Journal.

 

#4 – BIG DATA + AGILE = SUCCESS

“The longer you take to find the data, the less valuable it becomes.” – Wired.

With recent advancements in technology, more emphasis is being placed on data agility and the importance of data-driven insights in real-time. “How fast can you extract value from your mountains of data and how quickly can you translate that information into action?” – tdwi.org.

Ian Abramson, former Director at EPAM Systems, describes the alignment of Big Data and Agile as “the infrastructure and framework to be successful.” He then goes on to talk about how this alignment enables focus and a clear picture of how to get from A to B. “ What is the question, what is the success factor, how will we get there, and who will be involved?”

At the 2016 International Conference on Ambient Systems, Networks and Technologies (ANT), experts in the field of Big Data were asked, “ What do you think is most important in the management of Big Data projects?” Interestingly, respondents rated three out of the Four Values of The Agile Manifesto as the highest in their answers, which were: cooperation with customers, people & communication, and working with software over comprehensive documentation.

 

#5 – SKILL-UP OR MISS OUT

“Is the world going to become a place in which automation is everywhere yet employment is scarce?” – Michael Grothaus: The Hanbury Literary Agency.

According to KPMG’s 2016 CIO Survey, data analytics is the most in-demand technology skill for the second year running, but nearly 40% of IT leaders say they suffer from shortfalls in skills in this critical area. “Big Data training is beneficial in meeting the demands of Data Management, faster decision making, better understanding of customers and tapping into the right demographic.” – Vikrant Singh: Senior Manager at Xebia Group International.

In a recent article , Sophia Bernazzani, Marketing Manager at HubSpot says, “The fact remains that some jobs will be replaced by machines – it’s the essence of any industrial or technological revolution. The good news is; some jobs won’t be strictly replaced – they just might be adjusted to account for new technologies.”

So how do we skill-up and adopt these new technologies into our businesses? “By training those already with the company, businesses get to keep valuable team members that already have experience with the enterprise while giving them some much-needed skills.” – Rick Delgado: Enterprise Tech Commentator & Writer.

“Training employees can never be a liability. It is in fact an asset, an investment to the company.” – Big Data Trunk.

 

For more resources, please see below:

 

Data Integration

How To Integrate Data And Analytics Into Every Part of Your Organisation

Charting An Effective Big Data Strategy

Big Data: The Management Revolution

 

Data Quality

Beyond Volume, Variety & Velocity Is The Issue of Big Data Veracity

The Challenges of Data Quality Assessment In The Big Data Era

Big & Fast Data: The Rise of Insight-Driven Businesses

 

Cyber Security

How Big Data Is Improving Cyber Security

Big Data Security Analytics: A Weapon Against Cyber Security Attacks

 

Data Skills

The Importance of Employee Training

Businesses And The Big Data Skills Shortage

Big Data Jobs Are Out There: Are you Ready?

The Importance of Big Data Training to Your Data Analysis Growth

10 Jobs Artificial Intelligence Will Replace (and 10 That Are Safe)

 

Data Agility

Big Data and Agile: The Perfect Marriage

Agile Project Management And Its Use in Big Data Management