Category: Data Skills

Focus on Business Processes, Not Big Data Technology

2/11/2018

The rapid evolution of analytics has put a wonderful array of cutting-edge technologies at fingertips, from Spark and Kafka to TensorFlow and Scikit-Learn. And yet, despite this technological treasure trove, the vast majority of big data projects fail, according to analyst firms. So what gives? It’s likely a combination of factors, but one that stands out is that we spend too much time focusing on technology and not enough on business process, industry experts say.

Gartner analyst Nick Heudecker turned some heads last year when he said 85% of big data projects were failures, citing poor integration with existing business process, as well as internal policies, executive buy-in, lack of skills, and the ever-present security-governance issue. Other tallies of big data, data science, and advanced analytics projects have turned up similar statistics about the rather narrow odds of success in big data.

The fact is, losing at big data is a lot more common than wining. The human skillsets required to stitch together complex, largely open-source technologies into something that’s enterprise-grade and contributes value to the business are not easy to find.
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Big data analytics could be a powerful weapon against cyber security threats

27/9/2018

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With ever-growing technological innovations, the complexity of IT networks has risen sharply. Mobile devices, tablets, and wearable technology are generating huge amounts of data in real time that is getting exposed to cybercriminals. There are over 23 billion IoT devices connected to the internet today, which have created larger cracks for cyber attackers to exploit.

Information and business data are very important for any organization – they are increasingly taking note of the value of this data for their success in the current economy. This overwhelming reliance on information and data to make important decisions also requires protection of company and customer data. Organizations should implement strategies and may need to invest in testing security against penetration so that even the most sophisticated attacks can be foiled.

Today, the increase of cyber-attacks in terms of volume and complexity has made the traditional tools and infrastructure redundant.
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Big data baffles most board-level decision-makers

20/9/2018

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When board members in big firms make critical decisions about their organisations, it is almost always behind closed doors.
So exactly how and if senior leaders draw on big data factors in their decision-making is largely unexplained.

Researchers studied top-level decisions by board managers at 19 organisations in manufacturing, finance, consultancy, IT and air travel.
“Our study identified a shortfall in capabilities for dealing with the challenges of big data,” said Dr Ana Canhoto at Brunel Business School. “There is a gap in the knowledge and understanding organisations need, in order to avoid the cognitive biases and overloads big data can bring.”

The study, published in the Journal of Business Research, looked at how board managers think and act and the mental models and skills they use to weigh up big data.

Directors, it shows, recognise big data’s potential to improve their decision-making. But many admit feeling ill-equipped to do this, whether through their own technical skills or the new type of non-linear thinking needed.

The directors often found themselves reverting to old ways of thinking about their organisations or about how to use the information. This is hampered by sub-workers’ habit of only providing directors with simplified, ‘top level’ round-ups.
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Big data skills shortages – and how to work around them

6/6/2018

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Skills shortages are the perennial headache of CIOs everywhere, particularly when looking to develop leading-edge big data, analytics and artificial intelligence (AI) systems.

For the fourth year running, the Harvey Nash/KPMG CIO Survey has found that big data and analytics are top of the skills shortage critical list. This is having a significant impact on all organisations, with two-thirds of IT leaders saying it is preventing them from keeping up with the pace of change.

Given the newness of the discipline, it is not surprising that there aren’t enough skilled data scientists. Very few universities offer pure data science degrees (as opposed to computer science). Many schools still don’t even offer computer science at A-level or GCSE. It’s going to take some years before there are enough skilled data scientists in the workforce.
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The Impact Of Big Data Analytics On Leadership Development

17/4/2018

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Each year, U.S. businesses spend $20 to 50 billion on leadership training. With that kind of investment, one might assume that the state of American leadership is thriving. But the research tells a different story.
A recent Accenture survey found that only eight percent of executives felt their company was effective in developing leaders, and, in a survey by the Institute for Corporate Productivity, two-thirds of companies reported that they were ineffective at developing leaders.
It’s easy to see why some believe the leadership industry has failed us, but what’s causing this failure and what can be done about it? Harvard’s Barbara Kellerman suggests that the historic inability of organizations to harness leadership metrics and measures, leads to the disappointing outcomes found in leadership development. A company’s ability to precisely connect development to outcomes is critical to extracting return on investment from leadership training.
With the advent of machine learning, big data, and natural language processing, businesses can — and must — harness big data analytics to assess leader performance. Here are some ways that businesses and their leadership development practices will adapt to incorporate analytics.
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To reach its full promise, big data must begin with a clean slate

7/3/2018

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More than a decade has passed since we coined the term “big data,” and a decade in the tech world is almost infinity. Is big data now obsolete?
The short answer is that although big data in itself may still have its place for some apps, the focus has shifted to integrating data-driven insights into business applications, making sure they automate expensive manual operations or generate intelligent actions to help acquire new customers — that is, “actionable insights.” This requires very different tools and methodologies than the ones we used for “big data.”
Actionable insights require a fundamental change Common practice involves collecting data from various sources, then running multiple aggregation and join queries on it to create a meaningful, contextual data set. The output data is fed into machine learning algorithms that try to find common patterns or anomalies. In many cases, this is an iterative process involving trial and error, producing an artificial intelligence model that’s used for prediction or classification.
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Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics

23/11/2017

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In this article, I clarify the various roles of the data scientist, and how data science compares and overlaps with related fields such as machine learning, deep learning, AI, statistics, IoT, operations research, and applied mathematics. As data science is a broad discipline, I start by describing the different types of data scientists that one may encounter in any business setting: you might even discover that you are a data scientist yourself, without knowing it. As in any scientific discipline, data scientists may borrow techniques from related disciplines, though we have developed our own arsenal, especially techniques and algorithms to handle very large unstructured data sets in automated ways, even without human interactions, to perform transactions in real-time or to make predictions.

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Focus on Business Processes, Not Big Data Technology

Big data analytics could be a powerful weapon against cyber security threats

Big data baffles most board-level decision-makers

Big data skills shortages – and how to work around them

The Impact Of Big Data Analytics On Leadership Development

To reach its full promise, big data must begin with a clean slate

Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics

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The leading "Management Consultants in Big Data"
Business-Savvy, Vendor-Independent Experts
to help you thrive in the Big Data Jungle

UK - 0207 164 6260
USA - 415-500-9874
Or click here to contact us

Focus on Business Processes, Not Big Data Technology

Big data analytics could be a powerful weapon against cyber security threats

Big data baffles most board-level decision-makers

Big data skills shortages – and how to work around them

The Impact Of Big Data Analytics On Leadership Development

To reach its full promise, big data must begin with a clean slate

Difference between Machine Learning, Data Science, AI, Deep Learning, and Statistics

Categories

Archives

The leading ​"Management Consultants in Big Data"Business-Savvy, Vendor-Independent Expertsto help you thrive in the Big Data JungleUK - 0207 164 6260USA - 415-500-9874Or click here to contact us

The leading "Management Consultants in Big Data"
Business-Savvy, Vendor-Independent Experts
to help you thrive in the Big Data Jungle

UK - 0207 164 6260
USA - 415-500-9874
Or click here to contact us