Telmai Data Observability
TelmaiReviews from AWS customer
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Telmai offers a solution for managing data streams into your data warehouse
What do you like best about the product?
Monitoring the inflow of multiple data streams into a data warehouse can be extremely labor intensive especially if you are in an industry where data standards and transfer protocols are not well-established like in our business, advertising, where partners often change content format and structure without notice. Telmai’s software offers the power of AI with an ability to learn the intricacies and nuances of our data streams, flagging changes that represent anomalies that need attention.
What do you dislike about the product?
As with any AI product there is a need to spend time and effort training the system. There is also a learning curve for the data analysts so that they fully understand the true capabilities of the software. However, these requirements are not ponderous and still represent a significant reduction in time and effort versus trying to build similar capabilities in-house.
What problems is the product solving and how is that benefiting you?
We manage over 130 different data channels representing the full activities we have engaged in with our different ad campaigns. It goes beyond ‘simple’ bookkeeping. These data represent the raw material used for ROI analyses and all other efforts to validate the impact of these campaigns. Data capture and data quality are of paramount importance. Without a tool like this, we would be looking at the need for several additional headcounts strictly purposed for data monitoring and QA.
Fast and Easy Data Observability for the Enterprise
What do you like best about the product?
The tool was quick to set up, is cloud-native, has an intuitive UI and workflow, and generates ML-based anomalies out of the box without the need for complex configurations. It is the fastest tool to onboard data for observability, while also using its own external compute to keep costs from accruing in costly warehouses. It integrates well with our data source systems and the Telmai team has been able to work within our preferred communication tools to provide real-time support and advice. The tool is running smoothly in production and I use it every day.
What do you dislike about the product?
Management of large numbers of tables can be a hassle if not properly planned. There is some room for UI enhancements that would make that management easier.
What problems is the product solving and how is that benefiting you?
Telmai allows us to implement both business and general data quality rules on out critical data assets to ensure the highest quality data products for our internal and external customers. It is easy to onboard new data assets, customize rules for existing assets, and set up meaningful anomaly detection. We are able to use Telmai to run data quality tests, data regression tests, and provide assurance to our customers that the data is of the highest quality.
Streamline Your Data Monitoring with Telmai.
What do you like best about the product?
Telmai is a platform that appears to be designed to help data teams detect and investigate anomalies in real time. Using machine learning and artificial intelligence algorithms, Telmai can help identify unusual patterns and behaviors in data that may indicate potential issues or abnormalities.
What do you dislike about the product?
Telmai is a technological platform designed for real-time data monitoring, which may come at a higher cost than other more general-purpose data monitoring tools. However, the cost can be customized as per the utilization and need
What problems is the product solving and how is that benefiting you?
Telmai helps data teams proactively address problems before they become more significant issues or threats.
It is a valuable platform for data teams looking to proactively detect and investigate anomalies in real-time, potentially improving their ability to mitigate risks and respond to potential threats more quickly and effectively.
It is a valuable platform for data teams looking to proactively detect and investigate anomalies in real-time, potentially improving their ability to mitigate risks and respond to potential threats more quickly and effectively.
Seamless Data Manager
What do you like best about the product?
It is was way easy to use at it is a no-code Saas tool to start off with. Second, it was a seamless experience all together to manage large datasets and to get the entire info within seconds.
What do you dislike about the product?
The biggest drawback is that it does not provide API. This eventually does not help with integrations with major applications and services. They will need to work around it soon.
What problems is the product solving and how is that benefiting you?
We had it for a limited time, and it helped us a little bit when it came to collecting data and viewing it all under one umbrella. The dashboard was quite intuitive.
Great tool with low code
What do you like best about the product?
1. Easy to onboard.
2. Easy integration with different systems.
3. Simple yet interactive UI.
4. Overall improvement in the data quality.
2. Easy integration with different systems.
3. Simple yet interactive UI.
4. Overall improvement in the data quality.
What do you dislike about the product?
Since launch the product has improved a lot, there were certain issues in the starting but all thanks to responsive team to get them fixed in time.
What problems is the product solving and how is that benefiting you?
Overall process of customers deliverables was simplified.
Great tool to get a quick grasp on data inconsistencies and anomalies
What do you like best about the product?
For me, the biggest highlight is a very approachable team that was super engaged with us right from the beginning to understand our needs and wants. They are very open to feedback and can quickly act upon it.
As I led the data engineering team, my job was to build a modern and efficient data platform with highly automated data pipelines. New data ingestions happened with minimal development efforts but came with a trade-off that assumed correct and consistent data. Therefore a system that could catch data inconsistencies and provide a seamless data ingestion process is valuable.
Since our first collaboration, the product has matured and evolved a lot; I am happy to see new promising features that can help any data organization.
As I led the data engineering team, my job was to build a modern and efficient data platform with highly automated data pipelines. New data ingestions happened with minimal development efforts but came with a trade-off that assumed correct and consistent data. Therefore a system that could catch data inconsistencies and provide a seamless data ingestion process is valuable.
Since our first collaboration, the product has matured and evolved a lot; I am happy to see new promising features that can help any data organization.
What do you dislike about the product?
Nothing major. The data organization of every company and industry is very complex and different, so building one solution that works for everyone is a challenging feat.
What problems is the product solving and how is that benefiting you?
Detecting exact data anomalies and inconsistencies and sharing them with the stakeholders and partners to act upon is very useful.
AI-based quality monitoring and anomaly detection for complex data
What do you like best about the product?
A broad range of data sources including semi-structured sources, can be analyzed
Their no-code anomaly detection is a game changer and it makes for a very compelling data quality tool for my team
Their no-code anomaly detection is a game changer and it makes for a very compelling data quality tool for my team
What do you dislike about the product?
Nothing major so far. I have tried the product and will be adopting it down the road.
What problems is the product solving and how is that benefiting you?
Identifying issues in large volumes of data without writing complex rules and maintaining them over time.
Great Data Quality and observability with granular details and easy to share summary!
What do you like best about the product?
Analyze and detect in a timely manner data quality issues from a deep perspective. Having a variety of views makes it easier to detect issues, prioritize which ones to tackle, and size their impact.
Data Observability with great details is critical to us as a data company, as is being able to drill down to help the investigation and pinpoint the root cause, as well as high level summaries for non-technical teams to share to show improvements in data quality.
Data Observability with great details is critical to us as a data company, as is being able to drill down to help the investigation and pinpoint the root cause, as well as high level summaries for non-technical teams to share to show improvements in data quality.
What do you dislike about the product?
Everything has been going well so far. Each request has been taken into consideration by the product team.
What problems is the product solving and how is that benefiting you?
The ability to have an overview of all the data at a glance, with segments, and to apply different rules to validate the quality at the same time, simplifies my work as a Data Quality PM. I like that ML-based engine components are available out-of-the-box to speed up the setup process. To make the detection more precise, I need and enjoy the flexibility to create and implement my own rules easily.
Telmai helps solve the data observability and quality challenges!
What do you like best about the product?
A no-code on-boarding of the platform and can connect to our data source(s) in BigQuery seamlessly and options for alerting.
Telmai intuitively will learn from data patterns and finds the baseline to monitor drifts and any gaps to send alerts.
We not only know if the data pipeline ran successfully but also data is as expected - which is a huge peace of mind.
Telmai intuitively will learn from data patterns and finds the baseline to monitor drifts and any gaps to send alerts.
We not only know if the data pipeline ran successfully but also data is as expected - which is a huge peace of mind.
What do you dislike about the product?
Nothing specific, as with any startup entering a new space. Telmai is shipping new features and improvements at an awesome rate. It would be great for the team to continue the pace and add more features that help highlight the importance of data quality and observability!
What problems is the product solving and how is that benefiting you?
Telmai is helping solve two major problems for us. 1) When the data moves through the pipelines, we want to know if the run was successful and completed 2) The data that was transformed is accurate and as expected.
Are there any drifts in the attributes that we care and alert us if the difference is outside the normal range.
Are there any drifts in the attributes that we care and alert us if the difference is outside the normal range.
Accelerated our data validations and anomaly detection work-flow using Telmai
What do you like best about the product?
The Telmai team really understands the data quality challenges very well. As a Sr VP of Data engineering for me it was critical to ensure the quality of the data my team was managing had a high degree of confidence with the stakeholders. However I needed a more automated and ML based approach towards ensuring so we optimize the team productivity and also control the infrastructure and engineering spend on these initiatives low.
Telmai was super easy to on-board and get started. We specifically liked that the Telmai easily integrated with our heterogeneous data ecosystem and provided deep insights in days.
The visual and interactive UX made it easy to identify and resolve blind spots in data for both technical and non-technical users. Collaboration on tools was easy and I got better visibility into our data health. We specifically liked that the tool easily integrated with our heterogeneous data ecosystem and provided insights. Overall we were able to greatly accelerate our data quality journey using Telmai.
Telmai was super easy to on-board and get started. We specifically liked that the Telmai easily integrated with our heterogeneous data ecosystem and provided deep insights in days.
The visual and interactive UX made it easy to identify and resolve blind spots in data for both technical and non-technical users. Collaboration on tools was easy and I got better visibility into our data health. We specifically liked that the tool easily integrated with our heterogeneous data ecosystem and provided insights. Overall we were able to greatly accelerate our data quality journey using Telmai.
What do you dislike about the product?
When we engaged with Telmai, the product was in its nascent stage but the team is super solid and highly motivated to add capabilities and address gaps rapidly.
What problems is the product solving and how is that benefiting you?
Simplified the process of data quality review before we published the data to customers. In our case it was an internal customer - another department.
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