Machine learning and related developments form part of O’Reilly Media’s Ben Lorica’s predicted data trends<\/p>\n
It is very difficult for organisations to discern which tools will bring them the most benefit in the year ahead, and which issues they need to plan for, such is the\u00a0volume of technological choices available, data trends is no exception to this.<\/p>\n
New technological developments provide the platform for the next generation of innovation, as we\u2019ve seen with the evolution of \u2018Big Data\u2019 into advanced analytics, machine learning and artificial intelligence. How can businesses navigate this increasingly-complex data landscape to make the wisest investments?<\/p>\n
Here is our guide to the top seven data trends that should be on every organisation\u2019s radar for the year ahead.<\/p>\n
We recently conducted research which found that 85% of respondents said they already had some of their data infrastructure in the cloud, and other surveys of IT executives reveal that many are planning to increase their investments in Software as a Service (SaaS) and cloud tools.<\/p>\n
Next year, cloud migration will be fueled by the option of new cloud technologies, such as serverless and containerisation. Meanwhile, the choice of partners will also grow as vendors and popular open source data projects make their offerings easier to run in the cloud.<\/p>\n
For most companies, the road toward machine learning (ML) involves simpler analytic applications. This is good news because ML demands data, and many of the simpler analytic tools that precede ML already require data infrastructure to be in place. The growing interest in ML will spur companies to continue to invest in the foundational data technologies that are required to scale ML initiatives. This includes items like data ingestion and integration, storage and data processing, and data preparation and cleaning.<\/p>\n
Privacy was one of the defining issues of 2019, from the advent of the GDPR to the Cambridge Analytica scandal. We can therefore expect to see an increased focus on tools for privacy-preserving analytics. Organisations will begin to identify and manage risks that accompany the use of machine learning in products and services, such as security and privacy, bias, safety, and lack of transparency.<\/p>\n
\nFrom data storytelling to using data for good, James Eiloart from Tableau gives his take on the top trends in harnessing data as we head into 2019.<\/a><\/p>\n<\/blockquote>\n
Making machine learning sustainable<\/strong><\/h3>\n
Early indications are that many organisations are \u2013 wisely \u2013 focusing their first forays into machine learning projects on use applications designed to improve their most mission-critical projects. For example,\u00a0financial service companies are investing ML in risk analysis, telecom companies are applying AI to service operations, and automotive companies are focusing their initial ML implementations in manufacturing<\/a><\/u>. This is also reflected by the emergence of tools that are specific to machine learning, including data science platforms, data lineage, metadata management and analysis, data governance, and model lifecycle management.<\/p>\n
Data trends that need culture: Building a data culture<\/strong><\/h3>\n
In\u00a0a recent O\u2019Reilly survey<\/a><\/u>, we found that the skills gap remains one of the key challenges holding back the adoption of machine learning.<\/p>\n
With the average shelf life of a skill being less than five years and\u00a0the cost to replace an employee<\/a><\/u>\u00a0estimated at between six and nine months of the position\u2019s salary, there is increasing pressure on tech leaders to retain and upskill rather than replace their employees in order to keep data-led projects on track. We are also seeing more\u00a0training programmes aimed at executives and decision makers<\/a><\/u>, who need to understand how these new ML technologies can impact their current operations and products.<\/p>\n
Businesses are realising that investment in technology is not enough \u2013 they need to build a data culture throughout the organisation, and we\u2019re already seeing businesses\u00a0creating centres of excellence<\/a><\/u>\u00a0as they strive to foster a data-first mindset throughout the organisation.<\/p>\n
\nData is an organisation\u2019s greatest asset, but moving into 2018 it\u2019s significance to an organisation will grow<\/a><\/p>\n<\/blockquote>\n
Data trends we have been waiting for: IoT leaves the drawing board<\/strong><\/h3>\n
A few years ago, most Internet of Things (IoT) examples were still at the theoretical stage. Thanks in part to the rise of cloud platforms, cheap sensors, and machine learning the IoT is now poised to leap off the drawing board and into our lives. Beyond the smart cities and connected consumer devices that have dominated most IoT discussions so far, we\u2019ll still start to see other interesting use cases involving closed systems (factories, buildings, homes) and enterprise and consumer applications.<\/p>\n
Automation<\/strong><\/h3>\n
The increased pace of machine learning and analytics adoption will only be possible with scalable tools that enable data scientists to tackle many more problems and maintain more systems. This will lead to more process automation, including data preparation, feature engineering, model selection, and hyperparameter tuning, as well as data engineering and data operations. There are already some early\u00a0applications of machine learning<\/a><\/u>\u00a0aimed at the partial automation of tasks in data science, software development, and IT operations.<\/p>\n
\nQuantum Computing will render much of today\u2019s encryption unsafe, says Dr. Andrew Shields, Cambridge Research Laboratory of Toshiba Research Europe, but Quantum Cryptography could be the solution<\/a><\/p>\n<\/blockquote>\n
Overall<\/strong><\/h3>\n
If there is a unifying theme to these seven trends, it is that culture, skills and processes are now as crucial to strategic success as any single technology. Businesses that invest in building these foundations will be those with the best chance of success in the years to come.<\/p>\n
Ben Lorica, is the Chief Data Scientist at\u00a0O\u2019Reilly Media, Inc<\/a><\/u>. and Program Director of both the\u00a0Strata Data Conference<\/a><\/u>\u00a0and the\u00a0Artificial Intelligence Conference<\/a><\/u><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"
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