Big Data Solutions

Big Data Solutions

We are in a digital world of instant expectation. With the arrival of various mobile applications, Internet of Things (IoT), social apps, public web access, etc., the data sets have become massively large and complex.

‘Big Data’ – is the term given to such mammoth size data sets. Big Data is all about data gathering, analyzing, and probing very large data sets to uncover hidden patterns, unidentified correlations, and understanding customers’ preferences to improve business operations.

The concept of Big Data also have became a need of the hour with the expansion of industries such as finance, retail, advertising, telecommunications, utilities, healthcare, and pharmaceuticals. Defense and intelligence is also one of the areas where Big Data solutions have become essential.

In Big Data, the data is gathered in the form of structured data, unstructured data and semi-structured data format. Such massive data can be stored in Hadoop distributed file systems (hdfs), which is developed by Apache Hadoop.

Hadoop is an open-source software solution having the capability to store and work with Big Data. The variety of tools available in Hadoop assist in distributing the data processing load required to process massive data sets across a few to thousands to million computing nodes at a given period-of-time. In addition, Microsoft’s COSMOS, and SCALA is also used in understanding the massive large data sets.

Big Data is majorly classified into four sections:

  • Volume: the data at rest (just a gathering or accumulation of data)
  • Velocity: fetching data for the query (data being generated, collected and analyzed)
  • Variety: different types of data (structured data, unstructured data, and semi-structured data)
  • Veracity: segregating quality data or authentic data (it comprises of uncertain data, inconsistent data, incomplete data, deception data, etc.)

8 components of Big Data:

  • HDFS - (Digital data and its file system)
  • MR (MapReduce) – compiling and organizing (mapping) data sets
  • SQOOP – It is the combination of SQL + Hadoop for data processing
  • HIVE – Data ware house
  • HBASE – (No SQL components)
  • OOLIE – defines work flow
  • FLAME – continuous data streaming
  • PIG - (predefined components used for processing data in MapReduce)

Core Competency in Big Data

Big Data analysis has become essentially important for Software Development company Cloud-based technologies, artificial intelligence, machine learning and data science are the discovered potential areas which require expert data analyzing and data mining professionals. These areas are helping companies in analyzing the value chain of business and about the gain insights..:

Shriv ComMedia Solutions with its core capacities is ready to handle the huge requirements of Big Data analysis and data processing projects coming up from different fields and industries.

Our professionals are well-trained and skilled in the following areas:

  • Apache Hadoop
  • NoSQL
  • Machine Learning
  • Apache Spark
  • Data Mining
  • SQL
Mobilising the Enterprise
Application Modernisation
Outsourced Development