M
Mark Armstrong
Guest
Machine learning is a key part of the future of business—and not just for the enterprises that can afford an army of data scientists. We need access for all.
Machine learning, predictive analytics and Artificial Intelligence will soon rule the world… or so we’ve been hearing for the last two years. These technologies offer exciting opportunities, and the insights and customizations they provide will be—and in fact increasingly are today—at the heart of business success. However, for smaller organizations without big budgets, it can feel hard to get into the game. How can you compete without an army of data scientists at your disposal?
Collecting Data is Only a Start
Many small and midsize businesses do understand the potential that data can give them to optimize their business and win new customers. These businesses are well equipped to capture and store data from multiple sources, but this is only a start. To derive benefits from all this data, you must analyze and understand it. For many organizations, this is a massive challenge.
Data Analysis Should be Simpler
Data analysis is the first step in a successful machine learning program, but too often analytics is a secondary piece or add-on for a midsize organization’s development platform. Data mining and analytics platforms pile up, resulting in complexity and inefficiency.
On the other side of the equation, larger enterprises are harvesting their data and hiring data scientists to analyze their data and build custom advanced automation and predictive models. This requires an enormous investment of time and resources that is simply not realistic for smaller businesses.
In both cases, the process of applying data science is complicated—more so than it has to be.
Data Science for Business Users
Data analysis should be a central part of an app development platform, and should be able to be used by both IT and non-IT staff. Line of business managers such as CMOs, CFOs and COOs should be able to build and deliver powerful applications through the same platform—without requiring coding skills.
Analytics solutions must be designed with decision-makers in mind, letting them build, scale and protect mission-critical applications with cognitive capabilities that are flexible enough to continuously evolve with the organization.
Unlock Your Data with the Right Platform
It’s critical to choose a technology platform that doesn’t just meet the needs of today, but will empower you for the long run. As I recently told Computerworld, technology providers need to open the conversation and raise awareness about the benefits of data science, and then help SMBs realize them.
At Progress, we’ve been providing businesses with the technology they need to develop and deploy their applications for over 35 years, and we pride ourselves on delivering legendary support. As data science and cognitive-first applications grow in importance, we will be there to democratize it, making sure you understand the value to your business and stay ahead of the competition.
Continue reading...
Machine learning, predictive analytics and Artificial Intelligence will soon rule the world… or so we’ve been hearing for the last two years. These technologies offer exciting opportunities, and the insights and customizations they provide will be—and in fact increasingly are today—at the heart of business success. However, for smaller organizations without big budgets, it can feel hard to get into the game. How can you compete without an army of data scientists at your disposal?
Collecting Data is Only a Start
Many small and midsize businesses do understand the potential that data can give them to optimize their business and win new customers. These businesses are well equipped to capture and store data from multiple sources, but this is only a start. To derive benefits from all this data, you must analyze and understand it. For many organizations, this is a massive challenge.
Data Analysis Should be Simpler
Data analysis is the first step in a successful machine learning program, but too often analytics is a secondary piece or add-on for a midsize organization’s development platform. Data mining and analytics platforms pile up, resulting in complexity and inefficiency.
On the other side of the equation, larger enterprises are harvesting their data and hiring data scientists to analyze their data and build custom advanced automation and predictive models. This requires an enormous investment of time and resources that is simply not realistic for smaller businesses.
In both cases, the process of applying data science is complicated—more so than it has to be.
Data Science for Business Users
Data analysis should be a central part of an app development platform, and should be able to be used by both IT and non-IT staff. Line of business managers such as CMOs, CFOs and COOs should be able to build and deliver powerful applications through the same platform—without requiring coding skills.
Analytics solutions must be designed with decision-makers in mind, letting them build, scale and protect mission-critical applications with cognitive capabilities that are flexible enough to continuously evolve with the organization.
Unlock Your Data with the Right Platform
It’s critical to choose a technology platform that doesn’t just meet the needs of today, but will empower you for the long run. As I recently told Computerworld, technology providers need to open the conversation and raise awareness about the benefits of data science, and then help SMBs realize them.
At Progress, we’ve been providing businesses with the technology they need to develop and deploy their applications for over 35 years, and we pride ourselves on delivering legendary support. As data science and cognitive-first applications grow in importance, we will be there to democratize it, making sure you understand the value to your business and stay ahead of the competition.
Continue reading...