If you learn how to scale Artificial Intelligence (AI), you can create platforms that can be run by both tech and business users to optimize your processes. But before you head down that path, you need to ask yourself this question: How do the best companies get there?
The phrase “predictive analytics” holds a lot of promises—about solving problems before they occur, better service outcomes, targeting scarce resources, supporting decisions and improving responses in time critical situations.
With so much opportunity available, how can government start to consider the risks and benefits associated with this technology?
Do you practice DevOps?
It is time to take complete advantage of its agility and responsiveness by including security as an integral part of the entire app life cycle.
Integrate and automate security in your DevOps practice
Many organizations aim to shorten their system’s development life cycle and provide continuous delivery with high software quality. Where DevOps combine a system’s software development and IT operations, the Security team catches the bug & vulnerability during the development stage so that the end sure won’t be facing any errors after the release of the application. It safeguards the application release and the company’s reputation in the public market.
There is a lot of hype around data. It is billed as a route to better citizen service, faster business decisions and overcoming enterprise silos. But it’s not that easy; every data decision is dependent on resolving the lack of trust, misalignment and data silos.
As outlined in our previous blog, Data virtualisation and efficiently exploiting the power of the information contained in an organisation comes with its own challenges. In this blog, I’ll outline some of the challenges I have experienced and give some tips on how to navigate your way through if you have similar issues.
Sean Gerety once said, the technology you use impresses no one. The experience you create with it, is EVERYTHING.
Data management is a complex issue. The Information Commissioner’s Office (ICO) registered multiple data breaches and losses in recent years – technology and process needs to support better mitigation for these risks of error and oversight releasing private citizen data to the outside world.
Data governance is not an IT strategy. It is a business strategy—an essential enterprise wide initiative that enables faster decisions and improves data quality. In the Public Sector, data governance must bring together key stakeholders across business and IT to link to enterprise outcomes and priorities. In this post, we’ll explore why data governance is important and explain how to implement it effectively in the public sector.
It is clear that intelligent automation can alleviate the pressure on public services in difficult times.
But what about the actual delivery of the project?
You joined the Public Sector to make a difference to people’s lives, to ensure that taxpayer’s money is well spent and to help shape the country’s future.
That just got a lot harder.