Cloud Insights

Prevent your data lake from turning into a data swamp

Build a light-weight efficient data lake on Cloud

The future of Service Providers will be driven by agile and data-driven decision-making. Service Providers in the connectedness industry generate data from various sources every day. Hence, integrating and storing their massive, heterogeneous, and siloed volumes of data in centralized storage is a key imperative.

The demand for every service provider is a data storage and analytics solution of high quality, which could offer more flexibility and agility than traditional systems. A serverless data lake is a popular way of storing and analyzing data in a single repository. It features huge storage, autonomous maintenance, and architectural flexibility for diverse kinds of data.

Storing data of all types and varieties in central storage may be convenient but it can create additional issues. According to Gartner, “80% of data lakes do not include effective metadata management capabilities, which makes them inefficient.” The data lakes of the service providers are not living up to expectations due to reasons such as the data lake turning into a data swamp, lack of business impact, and complexities in data pipeline replication.

Product Engineering

Move to technology-driven smart policing

Leverage predictive analytics to reduce crimes and burglaries by 30%

Today, the crime rates in most parts of the world are high, despite taking necessary measures. Reports by FBI reveals, “3.9% increase in the estimated number of violent crimes and a 2.6% decrease in the estimated number of property crimes when compared to 2014.” Due to this, the police forces globally are under tremendous pressure to leverage technologies such as predictive analytics, to draw insights from the vast complex data for fighting the crimes. It not only helps in preventing robberies and burglaries but also aids in better utilization of the limited police resources.

Fig. Predicting crime by applying analytics on data feeds from various sources

As per studies conducted by the University of California, crime in any area follows the same pattern as the earthquake aftershocks. It is difficult to predict an earthquake, but once it happens, the following ones are quite easy to predict. The same is applicable when it comes to crimes in any geographical area. Combinational analysis of the past crime data and other influencing parameters help in predicting the location, time, and category of crime.

With the increasing crime rates, globally the police forces are under tremendous pressure to leverage technologies such as predictive analytics to draw insights from the vast complex data for fighting crimes.


Observability: Looking beyond traditional monitoring

Gain critical insights into the performance of today’s complex cloud-native environments​

As businesses transition towards multi-layered microservices architecture and cloud-native applications, they often struggle to gain granularity with the traditional monitoring tools. In the traditional method, teams use separate tools to monitor the logs, metrics, events, and performance, hindering unified analysis. Monitoring tools do not give the option to drill down and correlate issues between infrastructure, application performance, and user behavior. Teams often use logs for debugging and performance optimization, which becomes very time-consuming. Static dashboards with human-generated thresholds do not scale or self-adjust to the cloud environment. As thousands of cloud-native services are deployed on a single virtual machine at any given time, monitoring has become cumbersome. Further, conventional monitoring relies on alerting only known problem scenarios. There is no visibility into the unknown-unknowns – unique issues that have never occurred in the past and cannot be discovered via dashboards.​

Businesses need to make their digital business observable such that it is easier to understand, control, and fix.  Hence, they must​ look beyond traditional monitoring. With observability, businesses can gain critical insights into complex cloud-native environments​.​ Observability enables proactive and faster discovery and fixing of problems, providing deeper visibility about issues and what may have caused them.

With observability, businesses can gain critical insights into complex cloud-native environments​.​

Operational Excellence

Accelerate cash flows by faster order processing

Managed Digital Transformation to reduce Order-to-Activate (O2A) cycle time and increase new business wins

The Order-to-Activate (O2A) process is at the heart of every business operation. Simply put, it refers to the end-to-end process of receiving, processing, and fulfilling a customer’s order. A smoother and more efficient order flow will allow the company to process more orders, thus allowing the business to grow more quickly.

The Order-to-Activate process cannot be conducted in isolation; it depends upon numerous roles, departments, and systems. For example, a typical digital service provider takes 15+ teams to traverse through 55+ systems to complete one order. These complexities and increasing inefficiencies in the O2A process leads to longer cycle time, delayed revenue realization, and higher cost.

The complexities and increasing inefficiencies in the Order-to-Activate process lead to longer cycle times, delayed revenue realization, and higher costs.

Businesses need to ensure that their business runs smoothly, and the orders are delivered efficiently and accurately, with minimal chances of error. Adopt the Managed Transformation Model to achieve long term sustainable business benefits like reduced cycle time, accelerated revenue, enhanced customer experience, and maximized cost savings. By doing this, a business can transform its operations holistically and address all the challenges in the O2A process.

Businesses can ensure a reliable and undisrupted high-speed broadband service by adopting the ‘Zero-touch service assurance’ framework. This framework enables continuous remote monitoring to detect connectivity issues proactively and provide automated resolutions.

The model encompasses transformation levers such as:

  • Agile Work Cell: Consolidates multiple functional roles into one hence, reducing the touchpoints in the O2A process. It ensures better control, promotes transparency and eliminates handoffs
  • Process Optimization & Automation: Analyzes the current performance and cycle time elongation factors to identify and implement improvement opportunities
  • Operational Accountability: Provides a Dashboard with end-to-end visibility into each order and the milestones. It also helps in governance, performance tracking and reporting
IT Agility

Minimize the backup failures in data centers

According to different analysts, “5% to 25% of the backup jobs are failing across various tiers of data centers”. This impacts data centers heavily in revenue loss and SLA-based penalties. Further loss of essential data deteriorates customer experience. Hence, data centers must identify the root cause and reduce backup failures. The top reasons behind backup failures in data centers are the lack of storage space, database permission issues, and linear processing of high-volume backup jobs. Data centers should leverage a unique solution strategy to eliminate these problems and create successful backups.

Fig: Proven approaches to minimize the backup failure rate

Around 5-25% of the backup jobs are failing across various tiers of data centers