Business intelligence and analytics tools can help companies recover from the COVID-19 pandemic and position themselves as leaders in the new year
COVID-19 has had an impact on customers, the workforce, operations, finances, and technology. Today and into the foreseeable future, companies will need to outmaneuver uncertainty by changing their course as circumstances change—sometimes multiple times.
"This requires them to reassess assumptions, re-evaluate scenarios, and strengthen their ability to sense and respond," according to Accenture.
Other things to check out:
10 ways supply chains can use analytics to access greater savings on indirect spend
Today, organizations are seeking efficient ways to not just understand their purchasing data – but to draw actionable conclusions from it. With the emergence of tabulating platforms and proprietary analytic systems in the past two decades, supply chains are getting caught in an overwhelming tsunami of "big data" – whereby data volume becomes a challenge in and of itself.
Yet, service agreements pose unique challenges, as every contract is customized to an organization's respective needs. For indirect spend with your third-party partners, a deeper level of sourcing expertise is required to understand where your opportunities lie.
Case Studies Apply Big Data Analytics to Public Health Research
December 10, 2020 - Researchers at Johns Hopkins Bloomberg School of Public Health have developed a series of case studies for public health issues that will enable healthcare leaders to use big data analytics tools in their work.
The Open Case Studies project offers an interactive online hub made up of ten case studies that use real-world public health data to research five crucial US public health challenges. The project will also provide tools and guidance on visualizing, testing, analyzing, and structuring data. The project is funded by the Bloomberg American Health Initiative.
Customer-centric automotive data analytics proves maturity
Automotive organizations have always been reliant on analytics to drive their products, but with the proliferation of data and the changing customer landscape, this dependence has only grown.
While the healthcare and banking industries are the drivers for analytics, the automotive industry is a close follower and maturing its adoption. Rather than building from the ground up, however, automakers have had to invest in their analytical maturity.
Automotive organizations are pushing their analytical capacity and working on their maturity. The market conditions have changed, and competition has only gotten fiercer while data availability has dramatically increased. As automotive organizations have shifted their perspective on analytics, data has simultaneously become more available.
Not to change the topic here:
Nintendo Switch: How to Turn Off Data Sharing via Google Analytics | NDTV Gadgets 360
With the latest software update, your Nintendo Switch has been sharing your player data via Google Analytics. Nintendo Switch system update to version 11.0.0 was released last week and the new software patch actually brought along some significant changes to the table.
However, amid all the cool new features, what's not cool is the fact that Nintendo has enabled a setting that shares your player data via Google Analytics. For better privacy, you should disable this.
Skin-interfaced microfluidic system with personalized sweating rate and sweat chloride analytics
Advanced capabilities in noninvasive, in situ monitoring of sweating rate and sweat electrolyte losses could enable real-time personalized fluid-electrolyte intake recommendations. Established sweat analysis techniques using absorbent patches require post-collection harvesting and benchtop analysis of sweat and are thus impractical for ambulatory use.
The primary objective of this work was to determine the clinical validity of a roll-to-roll manufacturable, skin-interfaced wearable microfluidic device with colorimetric sensors and a smartphone image processing platform in measuring regional sweating rate and sweat [Cl − ].
31 Data Science and Analytics Predictions from 24 Experts for 2021
“We'll see more data-driven companies leverage open source for analytics and AI in 2021. Open source analytics technologies like Presto and Apache Spark power AI platforms and are much more flexible and cost-effective than their traditional enterprise data warehouse counterparts that rely on consolidating data in one place–a time-consuming and costly endeavor that usually requires vendor lock-in.
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"More technology companies will adopt an open source approach for analytics compared to the proprietary formats and technology lock-in that came with the traditional data warehousing approach. This open analytics stack uses open source Presto as the core engine; open formats such as JSON, Apache ORC, Apache Parquet and others; open interfaces such as standard JDBC / ODBC drivers to connect to any reporting / dashboarding / notebook tool and ANSI SQL compatibility; and is open cloud.
Building Energy Management Systems (BEMS) Market - Global Trajectory & Analytics to 2027 -
COVID-19 Crisis Brings the Environment into the Spotlight. With Energy Management Being Vital for Saving the Environment, BEMS is Poised for a 12.4% Growth Run Over the Next 7 Years
The global Building Energy Management Systems (BEMS) is expected to reach US$8.4 billion by the year 2027, trailing a post COVID-19 CAGR of 12.4%, over the analysis period 2020 through 2027.
Building Energy Management System (BEMS) are sophisticated systems integrating hardware, software, and services with information and communication technologies for monitoring, automating, managing, and controlling the energy requirements of buildings.
Happening on Twitter
I would also note: Government debt at record high. Unemployment 7% (960k people). Underemployment 10.5% (1.4 millio… https://t.co/UNjXoHbycl TheKouk (from Canberra) Fri Dec 11 20:23:15 +0000 2020
HEADS UP: With "an explicit commitment to hire or promote 1 million Black Americans WITHOUT 4 yr degrees," Black bu… https://t.co/eDJQQH2uxn Sifill_LDF Fri Dec 11 13:02:35 +0000 2020
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