Skyera System

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BLOCKCHAIN CONSULTING

Softwares used for Big Data & Analytics

hadoop

Apache Hadoop

Apache Hadoop is a Java-based free software framework that can effectively store large amounts of data in a cluster.

hdinsight

Microsoft HDInsight

It is a Big Data solution from Microsoft powered by Apache Hadoop which is available as a service in the cloud.

nosql

NoSQL

NoSQL databases store unstructured data with no particular schema.

hive

Hive

A distributed data management system for Hadoop mainly used for data mining purposes. This runs on top of Hadoop.

sqoop

Sqoop

This can be effectively used to transfer structured data to Hadoop or Hive.

polybase

PolyBase

This works on top of SQL Server 2012 Parallel Data Warehouse (PDW) and is used to access data stored in PDW.

excel

Big Data in Excel

As many people are comfortable doing analysis in Excel, you can also connect data stored in Hadoop using Excel 2013.

presto

Presto

It is built to handle petabytes of data.

Services We Provide in Data Science

Business Intelligence & Analytics: We can assist you in greatly enhancing the functionality and efficacy of your BI (Business Intelligence) reports. You will notice a better user experience and provide business users more control whether this is lowering IT support costs or developing interactive reports with deeper competitive insights, meaningful dashboards, and scorecards.

Enterprise Data Warehousing: With the help of our enterprise data warehousing service, your firm can access data for aggregated views across departments and cross-business insight. With our years of expertise and knowledge, we constantly work to reduce all risks related to the adoption of new technologies.

big data analytics

Data Science: Our Data Science group is focused on solving problems and finding hidden patterns, in both structured and a wide variety of unstructured types of data (such as social media content, textual data, images, audio and video streaming). In addition, our group also provides distributed and significantly parallel Big Data and Stream processing solutions, as well as high-performance GPU-accelerated computing concepts.

Data Integration & Processing: When organisations implement enterprise-level information systems, the most frequent problems they run into are cross-system data integration and consolidation. We enable data consolidation from many sources, including CRM, ERP, and other corporate systems, using event processing, intensive parallel processing, and data distribution.

Big Data Developer vs Data Scientist

As we’ve already seen, the software engineer in charge of designing, constructing, and maintaining the pipelines that will utilise all of the gathered data for the analysis and insight creation procedures is known as the big data developer. However, data science is a complicated field to which other professionals bring their particular set of skills.
The Data Scientist, on the other hand, is in charge of looking at all the data and performing the analytical process to fully comprehend the context and derive the insight that will inform business decisions utilising the tools and programmes developed by the big data developer.
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