Dataeaze Systems

Introduce your business and what you do there.

I’m the founder of a marketing strategy company that works with tech companies to design their go-to-market campaigns.

What challenge were you trying to address with Dataeaze Systems?

We were looking at building a data crawler to extract information from various portals, which required an engine that would scrape websites, extract data from there, and then run AI libraries on top of that raw data to generate insight from that information.

What was the scope of their involvement?

The range of services that they provided was around Python development on the data crawling activity and working on the database side to store all the data in the backend, which was created using MongoDB. They also used UML tools to extract information and intelligence from that data.

What is the team composition?

There was a project manager and architect involved because this was a very heavy research and development project. There was a team of one or two developers. Our main interaction was with the architect and some of the developers.

How did you come to work with Dataeaze Systems?

We reviewed quite a few sites. We were looking for a company that had strong data engineering capabilities and AI capabilities. We also wanted someone that could adapt to working with us as a small to medium-sized company as we are.

It was a very complex domain to work with, not necessarily the scope as it’s naturally large, but it certainly required strong technical expertise to be able to deliver it. Someone had recommended Dataeaze Systems to us, and we started working with them.

How much have you invested with them?

In total, we’ve invested around $40,000.

What is the status of this engagement?

We started this project in November 2019, and it was completed in June 2020. From the support side, it’s an ongoing engagement.

What evidence can you share that demonstrates the impact of the engagement?

This is a very niche area in which we’re operating, and there are a lot of unexplored things that we could do. We were also working on a very limited budget, but overall, I would rate them a four out of five in terms of the quality of work and deliverables. They also understood the tools we were working with.

We keep adding new sites and more AI in the library.

How did Dataeaze Systems perform from a project management standpoint?

In terms of communication, they were excellent. Because of the research-oriented nature of the work, we weren’t very clear on timelines.

What did you find most impressive about them?

What sets them apart is their strong focus on the data engineering side. They have certain solution accelerators that help companies like us rate development sites.

Are there any areas they could improve?

I think cost always, for companies like us, is an issue. It is something that, if it can be done at a lower cost, would always help an organization like us.

Do you have any advice for potential customers?

Invest the maximum time and effort during the initial architecture design for the project to become seamless.

Be clear on what business objectives you have and incorporate them much earlier in the overall development phase, rather than reaching out to them later. If someone isn’t 100% on the technical side, collaborating with them at an advisory level is something I recommend.

Please describe your company and your position there.

As the CTO my role was to oversee all of software development for Software Division. It was a role that managed teams spread across 2 locations.

We are an industry-leading integrator of digital networks engaged in design and integration of digital networks. We support global telecom companies, cloud companies, citizen networks and large enterprises to deliver solutions for their fixed and wireless networks for current and future needs.

For what projects/services did your company hire Dataeaze Systems, and what were your goals?

Goal was to develop a first of its kind, Computer Vision system which is able to do anomaly detection on sensor data to identify these patterns in near real time and at a massive scale of ingesting millions of data points per second.

We understood the fiber optic side and the sensor side of the solution but were looking for a partner to help us with the data ingestion, data management and data analysis with AI-ML to help us build the complete product.

How did you select Dataeaze Systems and what were the deciding factors?

We ran thru a selection process looked at 3 vendors etc. Dataeaze was selected based on the capabilities they demonstrated in the POC which they performed well.

Dataeaze was selected based on the vision and plan they had for the product development post POC Dataeaze was selected due to the knowledge of the team members who displayed and discussed the POC Dataeaze CEO and Lead people are knowledgeable. Dataeaze was flexible in their approach to partner with us.

Describe the scope of work in detail, including the project steps, key deliverables, and technologies used.

Protoype / POC Agile releases 0.1, 0.2, 0.3, 0.4, 0.5 and then 1.0 and 1.1 HDFS, Kafka, Java, Python etc.

How many people from the vendor's team worked with you, and what were their positions?

About 7 to 10 persons were engaged at various points in time ... with the roles as below

• Data Architect: Responsible for Designing Data pipeline
• Sr. Data Scientist: To Stitch the algorithm and perform model building and evaluation
• Machine Learning Engineer: To develop the model
• Data Engineer: Analyze the Data
• Support Engineer: Provide L1 & l2 support during development and Post go live

Can you share any measurable outcomes of the project or general feedback about the deliverables?

Product was delivered in reasonable amount of time . Pivots and changes were handled responsibly Commitment to make the solution work. Many unknowns in the solution were fixed by Dataeaze. Overall 8.5/10

Describe their project management style, including communication tools and timelines.

Agile / daily stand-up which was a good thing. Reporting on a weekly basis Hybrid project management approach. Are very transparent with things where they stand. 

What did you find most impressive or unique about this company?

Turnaround Time for experiments New ideas and implementing them Estimation techniques and transparency

Are there any areas for improvement or something they could have done differently?

Are very transparent with things where they stand. But then not proactive to share the information - but when asked are very transparent .. so from 3 rd week onward I started asking deep questions.

Please describe your company and your position there.

I am consulting CTO for Anand Rathi Wealth Services and we provide wealth solutions to clients in the Ultra HNI and HNI space. All our systems are hosted on AWS and portfolio analytics is a key offering to our clients.

For what projects/services did your company hire Dataeaze Systems?

We hired the Dataeaze team to implement a big data processing pipeline using AWS EMR, Spark and mySQL. The tasks involved data ingestion from various operational data stores, aggregation and computation and creating data marts for analytics and BI.

What were your goals for this project?

Provide clients real time view of their portfolios with upto mark to market values, performance nos across various dimension - portfolio level, client level and family level. Similarly, the RM managing the client should be able to use the analytics to generate recommendations for portfolio action.

How did you select Dataeaze Systems?

We selected Dataeaze based on the solution they had proposed in the pre-sales cycle. Moreever they had a strong track record of doing similar work in the past and the team came across as highly skilled and techno functional experts.

Describe the project in detail.

We wanted to implement real-time data ingestion from our operational databases to compute the performance of all the client and RM portfolios, mark to market and aggregate the AUM at various levels for analytics; AWS EMR was the data platform with underlying HDFS and Spark based processing and the final output was directed into mySQL databases for reporting, BI and Analytics.

What was the team composition?

The Dateaze team comprised of 1 solution architect, 2 data engineers and 1 BI developer.

Can you share any outcomes from the project that demonstrate progress or success?

The entire solution stack is running in production. we are running dynamic EMR instances at 1/10th the earlier infra cost, our processing speed has increased more than 1000% largely because of the ability to spin as many containers as needed to process large chunks of data in parallel and updated portfolios are available to customers before start of business day at 9am IST. Earlier portfolios would get updated late afternoon - which seriously compromised customer experience.

How effective was the workflow between your team and theirs?

All workflow was managed through JIRA boards and sprints. we run 2-3 week sprints and the Dataeaze team had the required tasks, they attend the daily standups and all the SCRUM ceremonies. all work communication happens over Slack and all interactions over Zoom. So overall, it was very structured and smooth.

What did you find most impressive about this company?

Its a small boutique data engineering company, highly professional and structured in their approach, their expertise in what they do and their commitment to scope. The quality of their work and timeliness has been very good.

Are there any areas for improvement?

They should scale up their team.

Please describe your company and your position there.

Working for a multinational system integration based out in Japan. I am responsible for expanding our OpCos technical capabilities in the region in distributed computing, AI, etc.

For what projects/services did your company hire Dataeaze Systems, and what were your goals?

To create a data analytics and visualization system using AI and distributed computing tools. Seamless integration of AI technologies and distributed computing technologies while automating most of the tasks were objectives.

How did you select Dataeaze Systems and what were the deciding factors?

Their past experiences and eagerness to try new things including the great people working at Dataeaze.

Describe the scope of work in detail, including the project steps, key deliverables, and technologies used.

Requirement gathering to Development. Ansible, Docker, Apache Spark, Apache Hadoop, Delta Lake, MLflow.

How many people from the vendor's team worked with you, and what were their positions?

5 members: 3 engineers and 2 senior executives.

Can you share any measurable outcomes of the project or general feedback about the deliverables?

We decided to continue to work with Dataeaze in other projects as their work is well above the standards.

Describe their project management style, including communication tools and timelines.

Used email based communication in the project. They communicated relevant matters in time allowing us to finish the project as planned.

What did you find most impressive or unique about this company?

We were impressed by their understanding of multiple technologies and coming up with multiple solutions for a problem.

Are there any areas for improvement or something they could have done differently?

Nothing particular.