Friday, July 5, 2019
Business Intelligence and Analytics 24
1 8 Data Analytics Acquisitions That Will Re-Shape the Industry
https://solutionsreview.com/business-intelligence/data-analytics-acquisitions-that-will-re-shape-the-industry/
Big data is big business, and the marketplace for data analytics and business intelligence software is gushing with innovative providers and advanced technologies. The proliferation of enterprise data science has seen an already vibrant landscape grow even brighter, with continued interest from major players and outside firms looking to expand their product portfolios. With millions invested and billions in valuation, analytics and BI providers are emerging as some of the fastest-growing (and most profitable) companies on the planet.
2 Why It’s So Hard to Fight Instinct vs. Data in BI Decision-Making
https://www.smartdatacollective.com/how-big-data-changes-business-intelligence-decision-making/
In the days before robust business intelligence (BI) platforms existed, professionals usually had to rely on experience and gut instinct when making decisions. Now, data analysis tools can give solid conclusions gleaned from months or years of compiled information. Even so, the people who dig through data still have difficulty trusting what the data says and quieting their gut instincts.
3 A digital reality for oil and gas
https://www.energyvoice.com/oilandgas/202660/a-digital-reality-for-oil-and-gas/
Good data analysis can have a direct impact on operational efficiencies and the potential reduction in operating costs as well as improved production and hydrocarbon recovery.
4 Cloud-Based CRM System: Is it Safe and What are the Benefits?
https://datafloq.com/read/cloud-based-crm-system-safe-benefits/6541
From their humble beginnings back in the 1980s, CRM (customer relationship management) systems have come a long way to become what they are today.
5 What is the Impact of Data Science Automation?
https://www.ibmbigdatahub.com/blog/what-impact-data-science-automation
On June 12th, IBM debuted AutoAI, a new set of capabilities for Watson Studio designed to automate critical yet time-consuming tasks associated with designing and optimizing AI in the enterprise. As a result, data scientists can be liberated to execute more data science and AI projects in their organizations. Read more about AutoAI in the announcement.
6 How to Communicate Your SaaS Marketing Performance to Your CEO
https://www.business2community.com/marketing/how-to-communicate-your-saas-marketing-performance-to-your-ceo-02216140
Whether you’re giving an impromptu presentation or running the show in a recurring meeting, communicating your SaaS marketing performance to your CEO may have you on edge.
7 When Your Boss Is an Algorithm – New York Times Opinion
https://www.nytimes.com/2018/10/12/opinion/sunday/uber-driver-life.html
There are nearly a million active Uber drivers in the United States and Canada, and none of them have human supervisors. It’s better than having a real boss, one driver in the Boston area told me,”except when something goes wrong.”
8 The Benefits of Customer Lifetime Value: Why It Matters
https://www.business2community.com/customer-experience/the-benefits-of-customer-lifetime-value-why-it-matters-02215821
What do America’s longest running companies all have in common? They focus on the big picture: customer lifetime value.
9 Make your Data Talk! – Towards Data Science
https://towardsdatascience.com/make-your-data-talk-13072f84eeac
What is data, nothing but numbers. If we are not visualizing it to get a better understanding of the world inside it, we are missing out on lots of things. I.e. we can make some sense out of data as numbers, but magic happens when you try to visualize it. It makes more sense and it suddenly it becomes more perceivable.
10 Probability Distributions Every Data Scientist Should Know
http://www.datastuff.tech/data-science/5-probability-distributions-every-data-scientist-should-know/
Probability Distributions are like 3D glasses. They allow a skilled Data Scientist to recognize patterns in otherwise completely random variables.
In a way, most of the other Data Science or Machine Learning skills are based on certain assumptions about the probability distributions of your data.
11 4 Most Popular Alternative Data Sources Explained
https://www.kdnuggets.com/2019/07/4-most-popular-alternative-data-sources-explained.html
Yes, alternative data is the new game changer.
It’s data which is curated from a variety of non-traditional sources. Alternative data basically implies data that is created with the advent of connected devices, varied sensors, transactional systems, social networking sites and of course, the Internet.
12 Machine Learning Drives Skyrocketing Demand for Entry Level Python Cod
https://datafloq.com/read/machine-learning-drives-skyrocketing-demand-python/6539
Even professional engineers are often dismayed by the pace of change in the technology industry. One of the biggest examples is with the emergence of machine learning. Only a few years ago, very few people had ever heard of the term. Today, it is growing faster than ever. One study shows that the machine learning market will be worth over $19 billion by 2023.
