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Techbla collects real-time data from business, extract relevant informations and process the data
which helfs us to analyse the informations and help you to make perfect future


Share Data

Data sharing is the practice of making data used for scholarly research available to other investigators.Requirements for data sharing are more commonly imposed by institutions, funding agencies, and publication venues in the medical and biological sciences than in the physical sciences. Requirements vary widely regarding whether data must be shared at all, with whom the data must be shared, and who must bear the expense of data sharing.

Extract Data

Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration). The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to export to another stage in the data workflow.


Process Data

Data processing is, generally, "the collection and manipulation of items of data to produce meaningful information." In this sense it can be considered a subset of information processing, "the change (processing) of information in any manner detectable by an observer

Analyse Data

Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.


Predict Data

Predictive analytics encompasses a variety of statistical techniques from predictive modelling, machine learning, and data mining that analyze current and historical facts to make predictions about future or otherwise unknown events.


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application of Artificial Intelligence for your enterprise


Machine Learning

Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" with data, without being explicitly programmed.


Deep Learning

Deep learning is part of a broader family of machine learning methods based on learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised.


Neural Network

An Neural Network is based on a collection of connected units or nodes called artificial neurons.



Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups.



In the field of data management, data classification as a part of Information Lifecycle Management process can be defined as a tool for categorization of data to enable/help organization to effectively


Random Forest

Random forests or are an ensemble learning method for classification, regression and other tasks, that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes


Supervised Learning

Supervised learning is the machine learning task of learning a function that maps an input to an output based on example input-output pairs.


Unsupervised Learning

Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets consisting of input data without labeled responses.

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What Are Our Services

Our Services
data analysis
data assessment
decision analysis


Data science is all about collaborative efforts between different skill sets towards achieving a common goal. We are a startup which helps organizations cover the path from data storage, structuring,engineering to taking smart decisions based on that data. Basically we predict Decisions for you.

We have a small yet experienced, young yet interdisciplinary team of engineers, domain experts, project planners and analysts who have only one focus and i.e. to find the most optimal solution to a clients problem.

Our end goal is to create a bridge in the data river from where the client can walk from his problem to its solution. So, share with us your data so we can clean it up and act only the relevant information, analyse it. process it and predict a solution to your problem by guiding you on your decision making.

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