Data Analytics

Conduct Science puts your science in the fast lane to publication

What is Data Analytics?

Is the process and methodology through which data scientists draw useful insights by manipulating data. They gather, organize, analyze, and turn the raw data into intelligibly visualized information to assist and augment our decision-making abilities, which is not possible without an efficient record-keeping or data-generating system.

When the data is huge that exceeds our comprehension capacity in terms of structure and power, that is where modern computing and analytical constructs come into the frame. That is Data Science.

Our Data Services

Data Science

Data science extracts insights from data using math, statistics, and computer science. It helps solve complex problems, predict trends, and make data-driven decisions.

Data Analytics

Advanced analytics, and machine learning techniques are key to creating predictive models. Developers can work with your team to improve forecasting, customer classification, and many other activities.

Data Visualization

Data visualization communicates information clearly and efficiently via graphs, plots, and infographics. Expert data visualization designers can help your team make better decisions with data.

Data Managment

Involves organizing, storing, and analyzing data to ensure its accuracy, accessibility, and usability. It encompasses processes for data collection, storage, sharing, and preservation, enabling efficient collaboration and reproducibility in scientific research.

Big Data Services

Big data services encompass technologies and strategies for processing, storing, and analyzing large volumes of data. These services enable organizations to extract valuable insights, detect patterns, and make data-driven decisions from vast and diverse datasets.

Data report and more!

Solutions for analyzing and presenting scientific data effectively. Assist researchers and organizations in organizing, visualizing, and interpreting data, enabling them to derive valuable insights and communicate findings accurately.

What is the importance of Data Analytics?

The world of data analytics

Data analytics is crucial for improving business performance and efficiency. In the banking and financial sectors, it predicts market trends, assesses risks, determines credit scores, and detects fraud.

In healthcare, data analytics predicts patient outcomes, enhances diagnostic techniques, and allocates funding efficiently.

In scientific research, advanced analytic techniques help scientists identify trends in complex systems. Data analysts specialize in interpreting these trends.

Types of Data Analytics

Data analytics encompasses various approaches to examining data to

Diagnostic Analytics

Diagnostic analytics involves studying the data to determine the causes of correlations and trends between variables. It is the next step after descriptive analytics is done manually. This type is used to examine market trends, explain customer behavior, identify technical issues, and improve company culture. It helps analysts know why something has happened at this time.

Descriptive Analytics

The process of analyzing and interpreting the historical data to understand various changes that occurred in business over this period. This process helps analysts draw comparisons by using a range of historic data.

Predictive Analytics

Predictive analytics uses modeling techniques and statistics to make future predictions about the outcomes and performance of the business. It uses advanced analytics techniques like data mining, modeling, statistics, machine learning, and artificial intelligence to look at the historical and current data patterns and determine if they are likely to emerge again.

Prescriptive Analytics

Prescriptive analytics help analysts prescribe what move to make next to eliminate the future risks or take full advantage of a promising trend that is most likely to come in the future. It is used for making important investment decisions, lead scoring, content curation through algorithms recommendations, banking sector for fraud detection, product management, and marketing sectors for email automation.

Our Data Analytics Services

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Consulting Services

Basic Data Analytics Service

Data Analytics + Implementation

Consulting services involve providing expert advice, guidance, and support to organizations seeking to leverage data analytics effectively.

Involves fundamental processes aimed at understanding and extracting insights from data without delving into advanced analytical techniques.

Is a comprehensive service that not only involves analyzing data but also implementing actionable insights derived from the analysis to drive business improvements.

Data Science Packs

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Our Data Service Includes

Defining goals & requirements

All configurations work as a drag and drop so your experiment is easy to configure, change, and collect data easily

Datification

All configurations work as a drag and drop so your experiment is easy to configure, change, and collect data easily

Data Modelling & Computation

All configurations work as a drag and drop so your experiment is easy to configure, change, and collect data easily

Modeling Results & Data Analysis

All configurations work as a drag and drop so your experiment is easy to configure, change, and collect data easily

Data Results & Reports

All configurations work as a drag and drop so your experiment is easy to configure, change, and collect data easily

Customer Feedback & Final Delivery

All configurations work as a drag and drop so your experiment is easy to configure, change, and collect data easily

How We do it

Our Work Process?

  • Identify The Problem/ Searching a research goal

  • Data Exploration / Data Organization

  • Collect the Pertinent Data / Gather the required Data

  • Data Modeling / Data Analysis

  • Communicate Results / Data Visualization

Our Methods

Deep Learning

Object recognition and localization, style transfer.

Image synthesis/translation using GANs and VAEs

Image visual similarity detection, transfer learning

Creating Language models

Training custom word/sentence embeddings

Semantic question answering over a large corpus

Speech to Text, Speech Language Identification, Speaker identification

Improving performance: Distributed network training (across CPUs/GPUs)

Neural Networks (CNN, RNN, ANN, DNN)

Wireless Sensor Network

Iris Recognition

Object Detection

Emotion detection

Video Surveillance

Prediction Models

Image impainting

Recommendation systems

Computer Vision

Image Classification

Image Recognition & Processing

Disease Prediction

Number Plate Detection

Blur Detection

SVM Classifier

Machine Learning

Computer Vision

OpenCV

OCR

Keras

Scikit-image

Gesture Recognition

Car Number Plate Extraction

Matplotlib

Image Processing & Classification

Image Recognition

Face Recognition

Facial Expression Recognition

Object detection

Spicy

CNN

Gensim for text analysis and processing

Machine translation

Speech to text conversion

Text mining

NLTK

Textblob

Speech recognition

Text to speech conversion

Language modelling

Text classification & summarisation

NLP

Data Resources

What is Data Management?

What is Data Management? Data management is collecting, organizing, protecting, and storing the data created by an organization. The managed data is readily available in

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Data Science and Its Strategies

Back in the times, business intelligence, scientific computing, exploratory statistics, etc., were employed separately to perform the singular task. Then data science emerged, thanks to the number of renowned scholars that incessantly pushed the idea forward.

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10-Demystifying-Data-Science

Demystifying Data Science

Have you ever pondered the question, “what exactly is Data Science”? Why is it becoming increasingly popular? Or what even advanced analytics, or data mining for that matter, mean?

That’s exactly what we aim to explain in the following article.

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