Tag: Digital Transformation

A few years ago, Gartner’s global research and advisory firm predicted a significant change in the IT management landscape. The present IT environment is more data-driven, distributed, and changing. Thus, IT professionals and leaders felt a strong need to advance digital transformations with the help of artificial intelligence (AI), machine learning (ML), and other approaches that can automate key operations. Despite the increased attention to artificial intelligence for IT operations (AIOps) technology, IT teams and analysts may need help choosing the right tools that align with their needs. In this article, we will shed light on the top five AIOps platforms for seamless SaaS management and how to choose the right AIOps tools for your business.

The Role of AIOps in Digital Transformation

AIOps is a new technology that has the potential to revolutionize digital transformation. This technology brings machine learning and data analytics together to automate IT operations and manage the infrastructure that is required for digital transformation. AIOps allows you and your IT team to manage, monitor, and analyze large volumes of data in real time. It helps them identify patterns, predict performance, and detect changes in the system. This data can be used to make informative decisions about the change in the system, reducing downtime and improving efficiency. In short, AIOps play an essential role in helping businesses drive successful digital transformation. It not only saves time and money but also provides valuable insights that can digitally transform your business.

With software as a service (SaaS) management, IT professionals and managers can input data, study correlations, and set up automation according to their business needs. Yet, managing SaaS applications can be challenging without proper integration. Let’s take a glimpse at the strategies needed for seamless SaaS management:

Strategies for Seamless SaaS Management

Software as a service (SaaS) has revolutionized business operations through its cost-effectiveness, scalability, and remote support. Most companies assume that SaaS management requires no implementation as its delivery occurs through the Internet and plug-and-play, but this is not true. As complex as the implementation can be, it is worth it for your business. Here are some implementation strategies that can help you and your teams lead this process, irrespective of the company’s industry or size:

Choose the Integration Management Application

Select the correct integration management application that aligns with your business needs. Some popular options include LogicMonitor, Zluri, and many more, which have aided many companies with their SaaS management solutions.

To Know More, Read Full Article @ https://ai-techpark.com/best-saas-management-platforms/ 

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Hyper-automation is a new term for technology and other industries where automation is needed. According to Gartner, hyper-automation is one of the most trending technologies that will greatly impact the next few decades. The motive of hyper-automation is to cancel out the repetitive tasks and make the whole task automatic by creating bots to perform them. These tasks will be performed with the combination of robotic process automation (RPA) and other advanced technologies like artificial intelligence (AI). In this article, we will understand the key benefits and best practices of hyper-automation. We will also get a glimpse of how it will help the manager + title achieve organizational goals.

1. The Best Practices of Hyper-automation in Business

Hyper-automation is crucial to empowering businesses through digital transformation to build fluidity in organizations that are capable of adapting rapidly to change. With the increase in competition in the business world, hyper-automation needs to be understood and analyzed properly. Here are 8 tactical points that will lay a good foundation for strategizing hyper-automation:

1.1 Creating a Strategy

When implementing hyper-automation, C-suite levels should understand what kind of strategy or which department needs this approach. Thus, a well-thought-out plan is needed to start somewhere.

1.2. Building the Right Team

To run the hyper-automation approach, a team with an accurate set is needed. The team should consist of manager-level data experts and analysts for their expertise in technical and strategic knowledge.

1.3. Everything Needs to Be Documented

Right from the start, the whole process of implementing hyper-automation, from each progress to any improvements after using the approach, needs to be documented for future reference.

1.4. Conduct an Audit

Managers need to understand the current level of digital transformation in their business and identify the processes that still need to be automated. This audit generally contains KPIs and data collection, which will help in decision-making and creating a plan for the future.

1.5. Setting a Suitable Tech Stack

To get suitable technology tools in place, C-suites from the technology profession need to focus on varieties of real-time data to provide accessibility from different sources, such as data warehouses, structured data, and data analysts.

1.6. Executing Hyper-automation Strategies

Start collecting data and creating a data quality for establishing it in the data warehouse.

Establishing automated notifications across different departments in the organization so that stakeholders can be alerted about any issues that can be addressed.

Implementing AI and ML models and training them according to continuous improvement in the business.

To Know More, Read Full Article @ https://ai-techpark.com/hyper-automation-in-business-process/ 

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Hyper-automation is a new term for technology and other industries where automation is needed. According to Gartner, hyper-automation is one of the most trending technologies that will greatly impact the next few decades. The motive of hyper-automation is to cancel out the repetitive tasks and make the whole task automatic by creating bots to perform them. These tasks will be performed with the combination of robotic process automation (RPA) and other advanced technologies like artificial intelligence (AI). In this article, we will understand the key benefits and best practices of hyper-automation. We will also get a glimpse of how it will help the manager + title achieve organizational goals.

1. The Best Practices of Hyper-automation in Business

Hyper-automation is crucial to empowering businesses through digital transformation to build fluidity in organizations that are capable of adapting rapidly to change. With the increase in competition in the business world, hyper-automation needs to be understood and analyzed properly. Here are 8 tactical points that will lay a good foundation for strategizing hyper-automation:

1.1 Creating a Strategy

When implementing hyper-automation, C-suite levels should understand what kind of strategy or which department needs this approach. Thus, a well-thought-out plan is needed to start somewhere.

1.2. Building the Right Team

To run the hyper-automation approach, a team with an accurate set is needed. The team should consist of manager-level data experts and analysts for their expertise in technical and strategic knowledge.

1.3. Everything Needs to Be Documented

Right from the start, the whole process of implementing hyper-automation, from each progress to any improvements after using the approach, needs to be documented for future reference.

1.4. Conduct an Audit

Managers need to understand the current level of digital transformation in their business and identify the processes that still need to be automated. This audit generally contains KPIs and data collection, which will help in decision-making and creating a plan for the future.

1.5. Setting a Suitable Tech Stack

To get suitable technology tools in place, C-suites from the technology profession need to focus on varieties of real-time data to provide accessibility from different sources, such as data warehouses, structured data, and data analysts.

1.6. Executing Hyper-automation Strategies

Start collecting data and creating a data quality for establishing it in the data warehouse.

Establishing automated notifications across different departments in the organization so that stakeholders can be alerted about any issues that can be addressed.

Implementing AI and ML models and training them according to continuous improvement in the business.

To Know More, Read Full Article @ https://ai-techpark.com/hyper-automation-in-business-process/ 

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