5 Proven Ways Manufacturers Can Get Started With Analytics
46% of manufacturers agree that implementing and using data analytics is necessary to stay competitive and grow their businesses. 69% of manufacturing decision-makers believe analytics will be crucial for business success in 2020, with 15% considering it crucial today. 32% of manufacturers see the potential for analytics to improve supply chain performance and increase revenue. […]
What Matters Most In Business Intelligence, 2019
Improving revenues using BI is now the most popular objective enterprises are pursuing in 2019. Reporting, dashboards, data integration, advanced visualization, and end-user self-service are the most strategic BI initiatives underway in enterprises today. Operations, Executive Management, Finance, and Sales are primarily driving Business Intelligence (BI) adoption throughout enterprises today. Tech companies’ Operations & Sales […]
How To Get Your Data Scientist Career Started
The most common request from readers is how to further their careers in analytics, cloud computing, data science, and machine learning. I’ve invited Alyssa Columbus, a Data Scientist at Pacific Life, to share her insights and lessons learned on breaking into the field of data science and launching a career there. The following guest post is authored by […]
How To Improve Supply Chains With Machine Learning: 10 Proven Ways
Bottom line: Enterprises are attaining double-digit improvements in forecast error rates, demand planning productivity, cost reductions and on-time shipments using machine learning today, revolutionizing supply chain management in the process. Machine learning algorithms and the models they’re based on excel at finding anomalies, patterns and predictive insights in large data sets. Many supply chain challenges are […]
The State Of Cloud Business Intelligence, 2019
An all-time high 48% of organizations say cloud BI is either “critical” or “very important” to their operations in 2019. Marketing & Sales place the greatest importance on cloud BI in 2019. Small organizations of 100 employees or less are the most enthusiastic, perennial adopters and supporters of cloud BI. The most preferred cloud BI […]
Which Analytics And BI Technologies Will Be The Highest Priority In 2019?
82% of enterprises are prioritizing analytics and BI as part of their budgets for new technologies and cloud-based services. 54% say AI, Machine Learning and Natural Language Processing (NLP) are also a high investment priority. 50% of enterprises say their stronger focus on metrics and Key Performance Indicators (KPIs) company-wide are a major driver of […]
Tech Leaders Look To IoT, AI & Robotics To Fuel Growth Through 2021
30% of tech leaders globally predict blockchain will disrupt their businesses by 2021. IoT, Artificial Intelligence (AI) and Robotics have the greatest potential to digitally transform businesses, making them more customer-centered and efficient. 26% of global tech leaders say e-Commerce apps and platforms will be the most disruptive new business model in their countries by […]
Global State Of Enterprise Analytics, 2018
71% of enterprises globally predict their investments in data and analytics will accelerate in the next three years and beyond. 57% of enterprises globally have a Chief Data Officer, a leadership role that is pivotal in helping to democratize data and analytics across any organization. 52% of enterprises are leveraging advanced and predictive analytics today […]
Where Business Intelligence Is Delivering Value In 2018
Executive Management, Operations, and Sales are the three primary roles driving Business Intelligence (BI) adoption in 2018. Dashboards, reporting, end-user self-service, advanced visualization, and data warehousing are the top five most important technologies and initiatives strategic to BI in 2018. Small organizations with up to 100 employees have the highest rate of BI penetration or adoption […]
The Domo S-1: Does the Emperor Have Clothes?
I preferred Silicon Valley [1] back in the day when companies raised modest amounts of capital (e.g., $30M) prior to an IPO that took 4-6 years from inception, where burn rates of $10M/year looked high, and where $100M raise was the IPO, not one or more rounds prior to it. When cap tables had 1x, […]
