Ever imagined how big MNC’s like Google, Facebook etc deal with loads of Data ?
Big Data a challenge for today’s world!
In this fastest world of technology, each day huge amount of data generated. In 2020, it’s estimated that for every person on earth , 1.7 MB of data will be created every second!
In the last two years, over 90% of the world’s data was created, and with 2.5 quintillion bytes of data generated daily, it is clear that the future is filled with more data. Data is created by every click, swipe, share, search, and stream, proliferating the demand for big data analytics market globally.
Ever thought how they are stored, managed and manipulated? 90% will say, no!
Whilst it is clear that companies can benefit from this growth in data, executives must be cautious and aware of the challenges they will need to overcome, particularly around:
- Collecting, storing, sharing and securing data.
- Creating and utilizing meaningful insights from their data.
Despite of this, they perform our actions within a second that too with high speed and accuracy! Don’t they face management problem?
Make way for Big Data!
Yes, they do!
Companies are using Big Data solutions to keep up with the rapid growth of data pools. The technologies that are booming greatly in the recent times are Artificial Intelligence, Big Data, Cloud Computing among many others. Companies across the world from startups to mature tech players have already shifted to big data analytics. The storage which is scalable to a very large proportion at an inexpensive cost is one reason why big data analytics is so popular today.
What is Big Data?
Before we delve into the most common big data challenges, we should first define “big data.”
There is no set number of gigabytes or terabytes or petabytes that separates “big data” from “average-sized data.”
Data stores are constantly growing, so what seems like a lot of data right now may seem like a perfectly normal amount in a year or two.
In addition, every organization is different, so the amount of data that seems challenging for a small retail store may not seem like a
lot to a large financial services company.
Instead, most experts define big data in terms of the 3V’s: high volume, high velocity and wide variety.
But how do top technology companies leverage this big data to serve their customers? Let’s see.
Did you know that Google processes about 3.5 billion search queries on single day? Do you know that each request queries about pages numbering 20 billion? The user requests are processed in Google’s application servers. Google uses Dermel which is a query execution engine to run almost near real-time, ad-hoc queries from search engines.
Did you know that users of Facebook upload 500+ terabytes of data per day? To process such large chunks of data, Facebook uses Hive for parallel map-reduce operations and Hadoop for its data storage. Would you believe me if I say Facebook uses Hadoop cluster which is the largest in the world? Employees also use Cassandra which is fault-tolerant, distributed storage system aiming to manage large amount of structured data across variety of commodity servers. Facebook also uses Scuba to carry out real-time ad-hoc analysis on massive data sets. Hive is used to store large data in Oracle data warehouse. Prism is used to bring out and manage multiple namespaces instead of a single one managed by Hadoop. Facebook also uses many other big data technologies such as Corona, Peregine, among many others.
Oracle
There is an explosive growth like 12.5 billion devices which doesn’t include phones, tablets and PCs. This has helped to increase the research and development in the field of Internet-of-Things and in storage requirements which in turn require database management support. Oracle users use Oracle Advanced Analytics which requires Oracle database to be loaded with data. Oracle advanced analytics provides functionalities such as text mining, predictive analytics, statistical analysis and interactive graphics among many others. HDFS data can be loaded into an Oracle data warehouse using Oracle Loader for Hadoop. This feature is used to link data and search query results from Hadoop to Oracle data warehouse. Oracle Exadata Database Machine provides scalable and high-end performance for all database applications. Oracle is leveraging big data to mainly expand its business in Database management systems.
Other giants in big data
Using Hortonworks Data Platform, big data solutions based on Hadoop is used by Microsoft. Microsoft uses big data on its components like SQL server, HDInsight to better its applications like Excel, SQL Server Reporting Services (SSRS). This is just one among many applications deployed by Microsoft. To manage 1.5 billion retail items across its 200 fulfillment centers, Amazon expertly uses big data technologies. It’s an open secret that Amazon is the unbeatable player among cloud service providers. Many companies use AWS cloud services to run big data operation. Other companies who use big data technologies are VMWare, Teradata, Splunk, IBM, Pentaho, SAP, Tableau.
The future of Big Data industry
Big data industry’s market size in 2016 was $37.67. In 2017, it is projected to make $43.4 billion market. Do you know how much the market size will be in 2020? Experts and big data scientists project a staggering $60.91 billion market share. The explosion of unstructured data especially in social media networks has increased the need for big data solutions for data management. Spark seems to overtake Hadoop in big data processing as experts argue that it is 100 times faster in memory. As Google did with BigQuery, tech players are innovating new and improved big data technologies very rapidly. Big data is already combined with artificial intelligence, cloud computing and the resulting technologies from this process will be nothing short of disruptive. Companies across the globe are expertly utilizing big data analytics to drive good business to provide better service to users.
