Enterprise big data and analytics cuts through the hype to make sense of data collection, storage, management, dissemination and discovery technologies, all employed collectively as a means of realizing corporate efficiencies and uncovering business opportunities.
• Analysis isn’t enough anymore. To be truly data driven, organizations also need synthesis.
• The analysis-synthesis duo can thrive if supported by a handful of conditions and practices within the organization.
The recent QlikWorld Online conference came and went with no new public roadmap, but it did offer something better: an intriguing vision of an analytics trend that’s built on a handful of new requirements — which altogether stand as a row of streetlights for the analytics industry to portend a new road.
Understanding data depends on the knowledge brought to it.
It’s stylish these days to be ‘data driven’ even while almost no one talks about what that really means. Data is just a proxy, the spokes on the wheel, the shorthand for what’s really going on. What’s the real driver?
During a blizzard, for example, we may talk about degrees Fahrenheit or Celsius. But that’s shorthand for the cold and snow, which is what actually drives decisions about what to wear or whether to go out at all.
• IBM Call to Code program builds momentum via prestigious partners and 300,000 global coders.
• IBM Cloud and Watson (AI) services are available to coders via open-source software (OSS) tools.
The power of technology to help solve real-world problems is perhaps most eloquently illustrated through the three winners of the COVID-19-related applications associated with IBM’s latest coding contest.
IBM’s two-year-old Call for Code Global Challenge campaign was initially launched in 2018 seeking innovative applications to address climate change. The program was expanded recently to include COVID-19, which spurred a massive response, including 1,000 developer registrations in a single day soon after being announced. Presently the program includes 300,000 developers across 168 countries. Continue reading “IBM Think: IBM Rallies Global Coders to Help Battle COVID-19”→
The world will find its way through the COVID-19 pandemic with data.
Data analysts will be among the ordeal’s heroes, and organizations with strong data literacy throughout will recover the fastest. Invest now in data literacy.
Doctors, nurses, and hospitals are the frontline heroes for the acute victims of the COVID-19 virus. But data is everyone’s compass — today as ‘the curve’ signals danger and eventually as the curve signals hope.
It’s a good time to understand data. Many organizations in the western hemisphere now face their greatest peril of our lifetimes. Those that survive will eventually face another daunting task: rebuilding in a new, different economy. Understanding data – knowing how to read it, organize it, prepare it, analyze it, and explain it – will be crucial. Continue reading “COVID-19: Don’t Miss This Moment – Invest Now in Data Literacy”→
• Mobile operators have been offering aggregated location data for several years, with limited uptake from sectors like tourism, retail, and transportation.
• Those big data analytics solutions could be very useful to authorities and essential services in fighting COVID-19.
Telecom providers are finding their networks used in different ways since the start of measures being taken to limit the spread of COVID-19. For mobile operators, that now includes the use of user location data analytics to help governments and other entities to understand—and fight—the spread of the virus.
In the last three or four years, mobile network operators have been investing in big data analytics technologies in order to leverage the potential value of the vast amount of network and user data they collect. Accessing the technology was the easy part: the availability of open source tools, hyperscale cloud platforms, and investments already being made in the telcos’ own digital transformations led to innovative solutions launching as early as 2014. Some players in Europe went further, acquiring analytics start-ups and digital consulting firms, helping them to offer both standardized solutions providing insights on visitors, events, and journeys, as well as customized projects. Continue reading “COVID-19: Using Mobile User Location Data to Understand and Mitigate the Pandemic”→
• VirusBlockchain deployed this week to identify and monitor COVID-19 free zones
• The blockchain monitoring system is backed by technology provider Qlikchain
This week the tech industry partnered with a public health consortium to launch a blockchain-enabled monitoring system aimed at keeping communities at bay from the COVID-19 pandemic.
The Public Health Blockchain Consortium (PHBC) announced the new system which monitors healthy, uninfected individuals as they move between locations in order to automatically identify zones that are safe or unsafe. The system is built on a blockchain solution which combines AI, geographical information systems (GIS), and real-time information systems provided by virus surveillance providers.
Companies that have yet to jump on the remote working bandwagon may have their hand forced due to the self-isolation and social separation measures put in place by their respective national governments.
We will undoubtedly see an uptick in the adoption of telehealth technologies, including remote monitoring.
On the 11th March 2020, the World Health Organization (WHO) declared COVID-19 (Coronavirus) a pandemic. As of writing, there have been over 130,000 cases reported across 123 countries, areas or territories and almost 5,000 deaths from the virus, which emanated from Wuhan in China. We have witnessed a wide variety of responses to the threat including mass self-isolation in Italy, travel bans, fiscal stimulus packages, health insurance policy allowances, business and school closures, and the cancellation of large events such as Mobile World Congress in Barcelona and HIMSS20 in Orlando, at which U.S. President Trump was scheduled to address the situation. Continue reading “COVID 19: Keep Calm and Corona On – A Global Perspective”→
• China has become a test bed for the potential to harness IT to manage and mitigate the effects of major health crises like the coronavirus.
• The widespread use of technologies like AI, big data, robotics, and blockchain raises questions about wider applicability, and concerns about longer-term governance.
Recent weeks have seen China emerge as a test bed for the potential to harness IT to manage and mitigate the effects of major health crises like the coronavirus. As of 11th March, China had almost 80,800 confirmed cases of the virus, also known as COVID-19, which had killed over 3,000 people. The economic impact of the virus has also been widely documented and includes disruptions to supply chains and lost business for countless shops, bars, and restaurants.
But China has also seen several applications of IT to help combat and manage impact of the virus. Examples include the use of workplace collaboration tools such as Alibaba’s DingTalk, Tencent’s WeChat, and ByteDance’s Feishu by businesses, hospitals, schools, and universities. These platforms enable various remote working arrangements, as well as the use of online classrooms, which support distance learning. Others include the provision of digital mapping tools. Baidu has created an epidemic map feature on the Baidu Map App that offers real-time location information about confirmed and suspected cases of the virus, as well as travel disruptions caused by enforced quarantines. Meanwhile, Tencent provides a self-examination tool on its WeChat platform to help users experiencing symptoms such as a fever or cough self-evaluate their condition and make any necessary arrangements. Tencent also maintains a map depicting clinics and hospitals that treat coronavirus patients. Continue reading “China’s Use of IT to Fight the Coronavirus Prompts Wider Applicability and Governance Questions”→
• Looking to build good artificiaI intelligence (AI)? Don’t let the speed and availability of open source frameworks, modules, libraries, and languages lull you into a false sense of confidence.
• Good AI needs to start with good data and good data needs to be ingested, registered, described, validated, and processed well before it reaches the ready hands of AI practitioners.
These are heady times. Enterprises have at their disposal both the raw materials and the necessary tools to achieve great things with AI, be that something grandiose as self-driving cars or unassuming as a fraud detection algorithm. The trouble with an abundance of materials (e.g., data) and tools (e.g., open source machine learning models), however, is speed. Speed kills, as they say.
For AI practitioners, this means learning to run before learning to walk by hastily automating decisions via AI models that are built on unsound data. With a few simple open source frameworks, modules, libraries, and languages, seemingly useful but ultimately erroneous predictions and conclusions can be readily drawn from any old data set in very short order. What’s the answer? More or better tools? No. As with most human problems, good old human knowhow and understanding are necessary. And that begins with data.