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Robotic Process Automation(RPA) and Benefits

What is Robotic Process Automation(RPA)

RPA is an automation technology for making smart software by applying intelligence to do high volume, repeatable and time-consuming tasks. RPA is automating the tasks of a wide variety of industries, hence reducing time and costs while increasing efficiency. It is a rule-based engine configured to replicate processes across various systems by using multiple data sources, and by applying complex policies and time-based rules. Therefore, Robotic Process Automation can improve the way organizations manage their IT investment portfolio, at least.

Here are some of the top Robotic Process Automation benefits for the businesses:

Reduced costs:

By automating tasks, cost savings of nearly 50% is a possible scenario, from productivity increase. Also, software robots cost less than a full-time employee.

Better Customer Experience:

Deploying RPA will free up your high-value resources, so you can focus more on customer success. Employees will have more time to invest their talents in more engaging and interesting work.

Lower Operational Risk:

By reducing or eliminating the human component, you will reduce errors due to lack of knowledge or tiredness, as a result RPA ensures a lower level of operational risk.

Improved Internal Processes:

In order to leverage Robotic Process Automation, companies are forced to define clear governance procedures. This leads to faster internal reporting, on-boarding and other similar activities.

No Replace for existing system:

RPA doesn’t replace your existing IT systems. One of the biggest advantages of using RPA is that it can be adapted to leverage your existing systems.

It acts as an assistant to any human as it triggers responses and communicates with other systems in the same way as humans do. In addition to that, chances of making mistakes is almost none and it’s quick. RPA is the thing which one should harvest quickly to gain a more competitive edge in the business.

Thank you Mihai Corbuleac, Senior IT Consultant at ComputerSupport.com for contributing.

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Silent Drains: How Poor Data Observability Costs Enterprises Millions

Let’s rewind the clock for a moment. Thousands of years ago, humans had a simple way of keeping tabs on things—literally. They carved marks into clay tablets to track grain harvests or seal trade agreements. These ancient scribes kickstarted what would later become one of humanity’s greatest pursuits: organizing and understanding data. The journey of data began to take shape.

Now, here’s the kicker—we’ve gone from storing the data on clay to storing the data on the cloud, but one age-old problem still nags at us: How healthy is that data? Can we trust it?

Think about it. Records from centuries ago survived and still make sense today because someone cared enough to store them and keep them in good shape. That’s essentially what data observability does for our modern world. It’s like having a health monitor for your data systems, ensuring they’re reliable, accurate, and ready for action. And here are the times when data observability actually had more than a few wins in the real world and this is how it works

How Data Observability Works

Data observability involves monitoring, analyzing, and ensuring the health of your data systems in real-time. Here’s how it functions:

  1. Data Monitoring: Continuously tracks metrics like data volume, freshness, and schema consistency to spot anomalies early.
  2. Automated data Alerts: Notify teams of irregularities, such as unexpected data spikes or pipeline failures, before they escalate.
  3. Root Cause Analysis: Pinpoints the source of issues using lineage tracking, making problem-solving faster and more efficient.
  4. Proactive Maintenance: Predicts potential failures by analyzing historical trends, helping enterprises stay ahead of disruptions.
  5. Collaboration Tools: Bridges gaps between data engineering, analytics, and operations teams with a shared understanding of system health.

Real-World Wins with Data Observability

1. Preventing Retail Chaos

A global retailer was struggling with the complexities of scaling data operations across diverse regions, Faced with a vast and complex system, manual oversight became unsustainable. Rakuten provided data observability solutions by leveraging real-time monitoring and integrating ITSM solutions with a unified data health dashboard, the retailer was able to prevent costly downtime and ensure seamless data operations. The result? Enhanced data lineage tracking and reduced operational overhead.

2. Fixing Silent Pipeline Failures

Monte Carlo’s data observability solutions have saved organizations from silent data pipeline failures. For example, a Salesforce password expiry caused updates to stop in the salesforce_accounts_created table. Monte Carlo flagged the issue, allowing the team to resolve it before it caught the executive attention. Similarly, an authorization issue with Google Ads integrations was detected and fixed, avoiding significant data loss.

3. Forbes Optimizes Performance