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Bhushan Patil

Bhushan Patil 
Solution Architect

Bhushan specializes in designing Data analytics platform, Cloud solutions & Mobile apps. His areas of expertise include strategic analysis, process improvements & relationship building.

He brings-in the right team - a combination of business understanding, solutioning and technology expertise - to solve your complex business challenges. Continue the conversation.

Page updated in Jan, 2021

Azure HDInsight and Data Lake Storage

Crunch Big Data on cloud with Azure HDInsight and Data Lake Storage

Azure HDInsight is a cloud-based distribution of Apache Hadoop. It handles vast amounts of unstructured or semi-structured data from IT assets. It provides on-demand scalability and includes programming extensions for handling Hadoop jobs using popular languages. HDInsight allows the deployment of projects using Spark, Kafka, and Hadoop. It includes Apache HBase for NoSQL data transactions, Apache Storm for stream analytics, and Apache Spark for large-scale data analytics.

HDInsight handles petabytes of structured and unstructured data without any hardware or installation cost. It allows the selection of Windows or Linux clusters for deploying Big Data solutions to the cloud. Our Data Analytics consultants are leveraging its capabilities to create Hadoop clusters in the cloud. What’s more, you can leverage the Power BI tool for rich data visuals and dashboards.

Azure Machine Learning

Implement powerful Cloud-based Analytics with Azure Machine Learning

Azure machine learning enables the transformation of data into intelligence. It allows you to build and deploy ML models quickly, selecting specific algorithms and extending support to open-source frameworks and tools, such as PyTorch, ONNX, Python, TensorFlow, and scikit-learn. Additionally, Azure ML backs MLOps to streamline the end-to-end ML lifecycle for faster innovation.

Enterprises are leveraging Azure machine learning for building, deploying, and sharing flexible machine learning solutions. These innovative machine learning solutions are capable of crunching the ever-increasing data volume. We tailor ML models to suit specific business needs by roping in Python, R or any of Microsoft's proven algorithms and are deploying models as fully managed web services.

Azure Stream Analytics

Leverage Azure Stream Analytics for processing real-time data streams on Cloud

Azure Stream Analytics allows the ingestion of real-time events from millions of data streams every second. It helps perform real-time analytics with high reliability on the data from IoT assets. Building real-time dashboards, establishing alerts, and implementing machine learning on multiple data streams for gaining invaluable insights is all possible with Stream Analytics.

Stream Analytics facilitates enterprises in ingesting and processing multiple events, comparing data streams, detecting anomalies, obtaining dashboard-views, and triggering condition-specific alerts, all in real time. Our Data Analytics consultants are leveraging its capabilities to enable enterprises with real-time insights from their devices and application data.

Azure Data Factory

Symphonize data collection and transformation with Azure Data Factory

Azure Data Factory is an on-cloud data integration service. It automatically establishes coordination among the services that collect raw data from various on-premises and cloud-based data sources. It enables creating, scheduling and managing data pipelines, along with monitoring the health of pipeline networks. It provides rich visualization features, pipeline lineages and interdependencies.

Data pipelines transform raw data for consumption by BI tools, like Power BI and applications. Saviant data architects then enable enterprises to monitor and manage their network of data pipelines automatically, for problem detection, rectification and intelligence acquisition.

See what our customers are doing with Azure Analytics

Data challenges using Azure Cloud

Global Energy company tackles its data challenges with Azure Cloud

With a robust data management platform, the company collects asset data from 450 wind turbines and stores more than 10 peta bytes of data per year, then generates real-time analytics on-the-fly.

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Azure ML based automated Fault Diagnostic system

Azure ML-based automated fault diagnostic system

Global supplier of instrumentation uses ML to build an automated system, which reduced the cost, time, and risk of asset repair and improved the accuracy of fault diagnosis.

Learn how we did it
Smart Meters goes cutting-edge with Azure solution

Leading supplier of smart meters is now on the cutting-edge

Using a smart water metering and analytics solution, this client now offers real-time visibility of water consumption for utilities and its customers.

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