In this week’s roundup, find out how digitalization is creating a competitive advantage for oil and gas data. Discover the power that marketing automation is having in the senior care industry and what AI trends are defining the future of data science. Plus, learn how advanced analytics is breathing new life in to six sigma initiatives. And finally, understand the ways machine learning can change incident management.
The competitive advantage of digitalized oil & gas data
By BOE Report Staff, contributing writer for BOEReport.com
Here are the top four reasons why digitalization should be the highest priority – to increase competitiveness for both you and your company.
Deploying strategic digitalization projects is the process of creating real-time data streams to enable better, faster decision-making and execution. This means piloting solutions that enable operators to obtain and disseminate critical information directly at their workstation, paperless.
Tapping Into The Power Of Marketing Automation In The Senior Care Industry
By Karina Tama-Rutigliano, contributing writer for Forbes.com
Traditional marketing strategies, community networking and good old-fashioned expertise have long been the marketing staples in the senior care industry. As digital transformation takes hold, digital initiatives, automated sales funnels and online advertising campaigns have gradually replaced manual marketing strategies.
4 AI Trends that Will Define the Future of Data Science
By Apoorva Komarraju, a contributing writer for AnalyticsInsight.net
Companies across the world are increasingly adopting AI for their smooth business operations. The technology unleashed its constructive potential during the onset of COVID-19 in performing a wide range of tasks that are complex and cumbersome for humans, bolstering employee productivity. Right from managing tasks ranging from planning, envisaging, and predictive maintenance to customer service chatbots, aiding data analytics, and more, businesses are extracting the maximum out of this disruptive technology.
The Future of Lean: Advanced Analytics Breathe New Life into Aging Six Sigma Initiatives
By Allison Buenemann, contributing writer for Automation.com
Decades ago, Lean and Six Sigma laid the groundwork for continuous improvement methodologies in the process and discrete manufacturing industries. Much like the process operations that Lean and Six Sigma have been applied to, the methodologies themselves have also been continuously improving.
Three Ways Machine Learning Can Change Incident Management
By Ajay Singh, contributing writer for DevOps.com
Incident management for important applications has many connotations, many of them negative. Most are well-deserved. Stress, panic, hurry, urgent, drop-everything, all-hands-on-deck, emergency, to name a few. Typically, there is a critical problem, ranging from complete failure to loss of certain functionality or performance. The problem or outage potentially means loss of revenue, loss of customers, negative social media commentary or bad reviews and more. Time is of the essence, dictating that the primary objective is fixing the incident as quickly as possible. Often, this means that symptoms or partial causes are mainly addressed rather than the underlying root cause.
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