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Apache Spark Development Company India

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Client Speaks - Testimonials for Aegis Software

Achieve Data Processing at the Speed of Business

Do you want to get accurate data insights at the right time for business developments?

Apache Spark is an open-source large-scale data processing engine that is built to create and work with machine learning algorithms, SQL, and process visual content. Apache Spark has various modules that make it easier to run the data analysis with very less memory consumption.

Aegis Softwares is an official partner of Apache Spark capable of leveraging the data science techniques in combination with the Apache Spark and its integrations to develop a platform it is efficient enough to stream the load of data over a few seconds. The main goal of our Apache Spark analytics solutions is to create a customized platform with fast data computing capabilities of Apache Spark. We also ensure the ease of the use of the system with quick access to the required data and its respective tools.

We are not just another Apache Spark development company; we are pioneers in big data with specialization in Hadoop technologies like HDFS, Map Reduce, Hive, and several other applications for easy significant data adoption. It equips us to create a holistic, big data analytics system for your company with the inclusion of the other tools along with Apache Spark.

Spark Development India

Where Can You Use Apache Spark for Big Data Analysis?

Aegis can help you to implement Apache Spark analytics solutions for different applications and business requirements. As an established Apache Spark development company in India, we have worked with organizations and startups from different domains by supporting their big data goals with Apache Spark. We have worked with businesses from:

  • Healthcare – Helping healthcare organizations to automate workflow, store patient data seamlessly, and provide better services by analyzing the patient records.
  • Retail – Run analysis on data collected from social media, search engines, websites, and other sources and use it to customize the website features and marketing strategies.
  • Finance – Enforce high-security measures to protect the credentials of customers and other sensitive business information through data analysis; provide customized services to the customers based on the historical data.
  • Media – Helps in customizing the platforms according to customer expectations, create content that converts and ranks better in the search engine algorithms.
  • Logistics – Identifying innovative ways to reduce the costs, achieve better efficiency in logistics with real-time predictive analysis using Apache Spark analytics solutions.
  • Energy – Leveraging the advantages of real-time data streaming to create better solutions for the end-users and gain a competitive advantage.

Apart from these sectors, we have also worked with companies that provide B2B services.

Our Apache Spark Development Services in India

As a part of our Apache Spark development, we provide a wide range of services for big data analytics, which includes:

  • Build a customized Apache Spark platform from scratch.
  • Automate data pipelines to minimize unnecessary delays.
  • Integrating the Spark platform with multiple data sources and create a data processing system to condition the data for analysis.
  • Build predictive models for specific big data requirements.
  • Incorporate new features to the platform according to the changing business needs.
  • Revamping Apache Spark and add new tools and modules to extract the best out of it.
  • Increase the speed of data processing by automating redundant applications and creating pathways that consume less memory.
  • Setting up the batch processing system to run large datasets with interactive models.
  • Setting up advanced analytics for data processing.
Apache Spark Development Our data experts are adept at working with the MLib, the machine learning library in Apache Spark, which simplifies the inclusion of machine learning in the data management efforts. Further, we also include the GraphX library, which is necessary for running graph computation and graph analytics, and Spark Streaming, which is essential if you want to process a large amount of data in a short time.

Why Sets Us Apart as Apache Spark Experts?

With our years of experience with Apache Spark and big data analytics in general, we know a thing or two better about leveraging our technical expertise to combat real-life data challenges. We have a pool of expert data analysts, data scientists, and data engineers who have worked with hundreds of other businesses to build and incorporate Apache Spark platform for their data needs.

Our wealth of information comes in handy at the times when you require fast data analytics solutions or when you have a hard puzzle that can only solve with data analysis. Furthermore, we have all the necessary tools and the latest software required to develop the Spark platform according to your business.

Therefore, our team will first listen to your requirements for Apache Spark solutions, analyze the current state of data utilization in the industry, create a better platform that beats your competitors and provide suggestions about putting data to use in innovative ways that have not yet been explored by the others in your industry.

If you want an expert data team on your side who has tackled the major data challenges since the past eight years, then Aegis it is! Just send out your requirements for Apache Spark in your organization to info@aegissoftwares.com. Get the worthy partner for your Apache Spark Development and big data analytics now and forget all about your data woes!

Frequently Asked Questions

Spark is an in-memory data processing framework which supports batch processing, stream processing, and interactive analysis. Data scientists often use it for data analysis. One can use Scala, R, Python, and Java on Spark. Spark is actively used for processing data collected through sensors (and other IoT objects) and solves a major part of the existing big data problems. It can also handle iterative machine learning very well.

When faced with this question, you need to talk about 5 basic points: Speed, Processing, Difficulty, Recovery, and Interactivity.

Spark is 100 times faster than Hadoop is. Apache provides, for real-time and batches processing whereas Hadoop supports Batch processing only. While Apache Spark is easy to work with (thanks to high-level APIs), Hadoop is very tough to learn. Apache spark allows recovery of partitions, while Hadoop is fault-tolerant. Hadoop has only Pig and Hive that are interactive, while Apache Spark has full-blown interactive modes.

Spark outshines Hadoop when dealing with real-time querying of data. Coming to Stream Processing, detecting frauds during live streams is possible using Spark. Sensor Data Processing is relatively much faster here. ‘In-memory computing’ is a huge benefit of Spark, reducing reading and writing time from the disk.

Spark supports Scala, Java, Python and R. Since Spark is written on Scala, Scala is the most popular amongst them to be implemented on Spark. Scala and Python both have interactive shells which can be accessed through these simple commands: ./bin/spark-shell or ./bin/pyspark.

Uber, Pinterest, and Netflix is their latest addition.

These were a few questions you’re bound to ask in a Spark interview. However, this list is not far from being exhaustive, as there are multiple concepts, from polyglots to BlinkDB that dived. However, if you have worked with Spark enough to build independent projects on it, you will be able to face the interview reasonably well.