Friday, July 24, 2020
Business intelligence and analytics 74
1 A commercial recovery for B2B companies during coronavirus
https://www.mckinsey.com/industries/advanced-electronics/our-insights/a-post-covid-19-commercial-recovery-strategy-for-b2b-companies
Leaders of B2B companies that primarily serve customers in sectors such as automotive, energy, mining, and telecommunications are trying to mitigate COVID-19’s economic fallout and human toll by ensuring workplace safety, increasing liquidity, and keeping supply chains moving. The pressures have been so intense that few are looking ahead to the return to work, when production lines will ramp up to full capacity. Those forward-thinking executives who do contemplate the recovery may have difficulty creating a solid plan, because COVID-19 has introduced unprecedented complexity into their operations.
2 Overcoming the Innovator’s Paradox
https://sloanreview.mit.edu/article/overcoming-the-innovators-paradox/
Having a great idea is essential to innovation, but that’s only half of what’s needed. Securing the resources to implement the idea is just as important — and potentially more difficult. The inventor Nikola Tesla, for example, came up with several transformative ideas — for electric induction motors, wireless telegraphy, radios, and remote control — but he died penniless because he couldn’t line up the resources to commercialize them. In contrast, Thomas Edison, arguably less brilliant, died wealthy and famous because he was good at both coming up with ideas and winning the necessary support to turn them into reality.
3 US push for global alliance against China hampered by years of ‘America first’
https://www.theguardian.com/us-news/2020/jul/24/us-china-mike-pompeo-america-first
The confrontation between the US and China is gathering pace with each passing week. In the past few days, the Chinese consulate in Houston has been shuttered amid allegations it was a spy hub, and the US mission in the south-western city of Chengdu was closed in retaliation, on similar grounds.
The FBI has started arresting Chinese researchers at US universities with suspected links to the People’s Liberation Army (PLA), one of whom temporarily took refugein the consulate in San Francisco, before surrendering.
4 What New Normal Should We Create?
https://sloanreview.mit.edu/article/what-new-normal-should-we-create/
We currently exist within a world that is unfrozen from the constraints of routine, habits, and norms. By leveraging this moment to explore, experiment, and learn, organizations and their community stakeholders have a unique opportunity to redefine the scope of their priorities and collective actions.
I use the word unfrozen deliberately. In 1947, behavioral psychologist Kurt Lewin proposed a process model of change that denoted three stages: unfreezing, change, and refreezing.
5 Antipatterns that are derailing technology transformations
https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/ten-antipatterns-that-are-derailing-technology-transformations
Most major organizations today have embarked on transformation programs in response to changes in customer, competitive, and regulatory landscapes. Whether the transformations are labeled agile, digital, or DevOps, their fundamental premise is to build value by establishing short, iterative, and continuous feedback loops between product and customers that dramatically improve both the product and its time to market.
6 COVID-19 is the asteroid that struck American small business
https://searchengineland.com/covid-19-is-the-asteroid-that-struck-american-small-business-338136
Small businesses (SMBs) are now in a Darwinian struggle for survival. The fallout from the COVID-19 pandemic is completely disrupting and reconfiguring the market, with some SMBs adapting and others calling it quits. This will have big implications for marketing and advertising as well.
In its Q2 economic report, Yelp paints a picture of increased consumer activity in late May and early June driving the growth of infections in states such as Florida and California. The report also quantifies the number of local businesses that are permanently closing.
7 How to Use Big Data to Perfect a Marketing Plan
https://datafloq.com/read/how-use-big-data-perfect-marketing-plan/8830
Ask any sports executive, and they’ll tell you that the biggest and most important shift in recent years is from using gut instinct to data for making important decisions. With so much information flowing around during the current digital age, you need to use this approach when it comes to your marketing strategy. Marketers in every industry and sector are using analytics and information to glean insights on client behavior and habits. This information will help you get a leg up on the competition. Here’s how you can use big data to perfect your marketing plan going forward.
8 Analyze-then-Store: The Journey to Continuous Intelligence
https://insidebigdata.com/2020/07/20/analyze-then-store-the-journey-to-continuous-intelligence/
This multi-part article series is intended for data architects and anyone else interested in learning how to design modern real-time data analytics solutions. It explores key principles and implications of event streaming and streaming analytics, and concludes that the biggest opportunity to derive meaningful value from data – and gain continuous intelligence about the state of things – lies in the ability to analyze, learn and predict from real-time events in concert with contextual, static and dynamic data. This article series places continuous intelligence in an architectural context, with reference to established technologies and use cases in place today.
9 Easy Guide To Data Preprocessing In Python
https://www.kdnuggets.com/2020/07/easy-guide-data-preprocessing-python.html
Machine Learning is 80% preprocessing and 20% model making.
You must have heard this phrase if you have ever encountered a senior Kaggle data scientist or machine learning engineer. The fact is that this is a true phrase. In a real-world data science project, data preprocessing is one of the most important things, and it is one of the common factors of success of a model, i.e., if there is correct data preprocessing and feature engineering, that model is more likely to produce noticeably better results as compared to a model for which data is not well preprocessed.
10 Recommender Systems in a Nutshell
https://www.kdnuggets.com/2020/07/recommender-systems-nutshell.html
When you search for a product on Amazon, the algorithm suggests other items with the note “Recommended for you, Kevin” or “Customers who bought this item also bought…”
Recommender systems predict the preference of the user for these items, which could be in form of a rating or response. When more data becomes available for a customer profile, the recommendations become more accurate.
11 The UK’s Huawei decision is emblematic of the new tech cold war
https://www.pharmaceutical-technology.com/tech/the-uks-huawei-decision-is-emblematic-of-the-new-tech-cold-war/
After months of prevaricating, the UK recently made the decision to lock Chinese telecoms company Huawei out of its 5G network. In January, the UK had decided to limit the company’s share of the network to 35% and keep it out of the sensitive ‘core’, but this decision was overturned after the US imposed new sanctions on the company, meaning it could no longer use US-made chips.
12 What I learned from looking at 200 machine learning tools
https://www.kdnuggets.com/2020/07/200-machine-learning-tools.html
To better understand the landscape of available tools for machine learning production, I decided to look up every AI/ML tool I could find. The resources I used include:
Various lists of top AI startups by the media
Responses to my tweet and LinkedIn post
People (friends, strangers, VCs) share with me their lists
13 4 Ways to Excel as a Female Data Scientist
https://www.informationweek.com/big-data/4-ways-to-excel-as-a-female-data-scientist/a/d-id/1338373
Glassdoor has ranked data science as one of the top 10 best jobs in the US every year since 2015. Here’s how you can stand out in this field.
From analyzing large volumes of data to building contact tracing applications or using machine learning algorithms to discover effective treatments for COVID-19 quickly, the demand for data scientists with diverse skill sets and backgrounds has soared.
14 Data Mining and Machine Learning: Fundamental Concepts and Algorithms: The Free eBook
https://www.kdnuggets.com/2020/07/data-mining-machine-learning-free-ebook.html
The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression.
15 The Bitter Lesson of Machine Learning
https://www.kdnuggets.com/2020/07/bitter-lesson-machine-learning.html
The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin. The ultimate reason for this is Moore’s law, or rather its generalization of continued exponentially falling cost per unit of computation. Most AI research has been conducted as if the computation available to the agent were constant (in which case leveraging human knowledge would be one of the only ways to improve performance) but, over a slightly longer time than a typical research project, massively more computation inevitably becomes available.
