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Are You Looking For An Experienced Data Science Team For Your Businesses?
Our Offerings
We configure customizable data analytics solutions to transform your enterprise data into intelligence and steer you to get great business outcomes.
Data And Analytics Strategy
Our data experts can map your analytics initiatives into quantifiable business outcomes with a data-driven approach.
Data Discovery & Augmentation
We deliver the 360-degree customer prospects by improving your assets with third-party data and predictive analytics.
Data Management & Beyond
On the extra edge of data integration and analytics, we advance with governance, monetization, and compliance.
Data Democratization
Our solutions allow employees to use custom, user-friendly tools that can embrace data and take you to the edge of AI.
The Step-By-Step Data Analytics Process
Data Cleansing
This step recognizes and improves the unstructured records into a dataset. The data may include unfinished, unreliable. incorrect data that requires to be reviewed and put in actual format with the support of data cleansing techniques.
Feature Engineering
This process helps to convert raw data into features that show a better solution to the underlying problem. it allows us to give flexibility, better results in the data analytics process.
Data Exploration
The data exploration process manages model preparation, evalution, estimation, and tuning, which provides robust data insights that allow our clients to make successful business decisions.
Case Study
Success Story
A subscription box based eCommerce platform that ships organically-grown succulents from a SoCal nursery to any address in the United States was looking to optimize their shipping process to be inline with daily weather forecasts so as to schedule the deliveries at the best port and at the best time of the day. The company ships 100K+ of succulents each week, to every state, all year long. Mindbowser helped the company to build a program that optimized its logistics operation and brought efficiency to its operations using data points.
Select Your Suitable Data Analytics Option With Us
Data Analytics As A Service
We offer analytics solutions that help our clients to receive first meaningful insights from the raw data within days. Our top-notch analytics solution reduces the burden of cost and time for developing and maintaining a considerable analytical solution.
Data Analytics Implementation
As a leading data analytics service provider, we are able to offer a time-effective solution that is sufficiently compliant according to your business objectives. Our experts can implement a data analytics solution to advance your business or entirely revamping the existing one.
Data Analytics Support & Evolution
Mindbowser can advance your existing analytical solution with an effective time frame by studying the current analytical setting, determining the stumbled blocks, and fixing problems that limit you from using data analytics.
We Produce 100+ Analytic Roadmaps Every Year Saving Costs For Our Clients With The Help Of Our Expert Developers, Agile Methodology, And More.
Technology
Our experts put statistical and mathematical methods and tools to invent solutions that help organizations automate processes, optimize in-and-out operation processes, and extract valuable data insights for your business.
Predictive Analytics
NoSQL Databases
Knowledge Discovery Tools
Stream Analytics
In-memory Data Fabric
Distributed Storage
Data Virtualization
Data Integration
Data Preprocessing
Data Quality
Why Mindbowser?
Our lean and agile team of full-stack data scientists, engineers, and application developers accelerate innovation and implementation of custom machine learning and AI products. We bring extensive cross-industry expertise backed by scientific rigor and deep knowledge of state-of-the-art techniques to design, build, and deploy bespoke AI solutions.
SOLUTION ACCELERATORS
Ready models that result in time and cost-saving
DOMAIN EXPERTS
We help you identify & validate viable use cases across your business, guide your model through to deploying your models into production
IN-HOUSE EXPERTS
A strong team led by ph.D. holders in data science and AI
FRAMEWORK AGNOSTIC
Our solutions are independent of the fremework. This means you can continue to explore new tools as well as choose different tools among open source and well as proprietary
360 DEGREE SERVICE
We cover the full spectrum of ML and AI that is required to get the right ROI for your business. This includes in-house data collection to create rule engines that are done by a single team. This means ypu have no multi-party dependencies
Frequently Asked Questions
Exploratory data analytics is a statistical approach that is used to analyze and produce descriptive graphical summaries. The most significant advantage of using EDA instead of a statistical model is that, with EDA, analysts are able to foresee what the data can reveal beyond the formal modeling.
Tools are primarily decided as per requirement. Major tools that we use are
- Tableau Public
- Qlikview
- R Programming
- Python
- SAS
- Microsoft Excel
- RapidMiner
- KNIME
- OpenRefine
- Apache Spark
Yes, we do. Our developers, too, are covered under NDAs and confidentiality clauses.
All our code goes through a quality audit and review by CodeGrip.tech.
The reports are available in an easy to understand format as part of the sprint.
We have SLAs defined for projects. This includes performance parameters for individuals as well as key goals for the overall project. We keep revisiting this SLA at regular intervals to ensure that we are in line with the plan. Any deviation is immediately fixed.
We provide you a technical project manager based out of the US or India to work directly alongside you. During the initial plan, our CTO, VP of Engineering, and CEO are involved too. Once the project journey is planned, the project manager is your main point of contact with a well-established escalation procedure.
The project manager keeps you updated as per plan on all the development information and acts as your primary quality analyst.
There is no one size fits all. We pick a tool based on the task. Usually, there would be a stack of different tools within an engagement.
In data science work, we usually used the following tools.
- Libraries: Pandas, Numpy, Beautiful Soup, JSON, SKLearn, Keras, Plotly, MatplotLib, Tableau, etc.
- Tools: Pycharm, Jupyter Notebook
We deal with structural and unstructured data like SQL, NoSQL, CSV, JSON, Flat Files, Images, etc.
The data size depends on the case to case basis, but generally, we handle data records in thousands to millions. We have worked with data in 100s of GBs.
The team comes from different backgrounds. We primarily focus on analytical thinking a proactive approach in Data Science. Our team members generally have a strong background in mathematics.
Insights
Check out our blog on trending topics on Data Science services and solutions.
Insights
Check out our blog on trending topics on Data Science services and solutions.
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