No doubt, there has been a great surge in data generation in the last decade. Big data has now become a major source for many global companies to bring innovation and growth like never before. Every major organization nowadays relies on data to bring new innovations, tools, and services to grow their brands and fulfill customers’ demands. That’s why the data is now collected more than ever. However, to analyze and manage the data correctly and effectively, there are certain tools and platforms that play an indispensable role. These platforms and tools help companies to store, process, and determine vast and complex data to make strategic decisions and new innovations.
Know How Big Data Platforms and Tools Work
In today’s digital world, top platforms and tools in big data analytics are used where extensive data is scrutinized and analyzed. Big data platforms have the elaborated and streamlined framework that help any organization to store, process, and analyze structured as well as unstructured data. These platforms provide a comprehensive ecosystem of advanced tools, technologies, and proper infrastructure to easily handle any volume and variety of data to help businesses worldwide to know new trends, customer demands, and optimize their business operations to a great extent.
There is a structured process that every big data platform follows:
- Collecting Data: It is the first step where all these platforms collect data from different sources such as social media, databases, sensors, etc. It’s collected using various methods, including web scraping, APIs, data feeds, and data integration tools. Once the data is collected, it’s stored in a centralized repository to be accessed and processed seamlessly.
- Processing Data: The next step is to process it and extract valuable insights from it. It involves cleaning, transforming, and aggregating the data using various technologies, including Apache Hadoop, etc.
- Analyzing Data: Now the data is analyzed and interpreted to take out the valuable insights from it using machine learning and data mining technologies.
- Quality Assurance: This step is all about the authentication of data and its quality. Here the data quality management and cataloguing techniques are involved.
- Data Management: Finally, the data is managed through storing, organizing, and retrieving large chunks. Here, big data platforms use different methods, such as data backup, recovery, and archiving, to manage data seamlessly.
What Are The Traits for Big Data Platforms?
There are multiple features of big data platforms, including:
- Data Storage and Management: It is the key feature of major big data platforms. Most big data platforms offer sturdy, scalable, and super-advanced storage solutions to handle any volume of structured or unstructured data. Along with that, there are several storage options, such as NoSQL databases, distributed file systems, data lakes, etc., to let companies store and organize data easily. Also, with the arrival of cloud-based storage options and advanced data management capabilities, one can now easily store data without worrying a little.
- Distributed Processing: It is also one of the important features that distributed the large data processing across various servers or nodes in a streamlined distributed computing environment. The feature helps businesses minimize the data processing time to achieve greater performance and productivity.
- Fault Tolerance: This feature enables big data platforms to function uninterruptedly even after hardware or software breakdowns. Since the risk of breakdown or failure is massive in data processing, the feature helps the platforms to prevent data loss and uninterrupted data processing and availability for real-time analytics and achieve missions.
Popular Platforms for Big Data
Nowadays, there is no dearth of big data tools and platform solutions. But, when it comes to the leading platforms and tools for big data, then they are:
1. Apache Hadoop
It’s the most trusted and popular big data platform with an open-source framework. It helps distribute and process extensive data clusters and offers a scalable and affordable solution to store, process, and analyze large chunks of structured and unstructured data.
Features
- It offers a distributed file system called Hadoop Distributed File System.
- It has an incredible processing engine, MapReduce, that helps in unmatched data processing across various clusters.
- Many renowned companies, such as Yahoo, Twitter, and Facebook, use this platform.
2. Apache Spark
It is also the most sought-after platform using a unified analytics engine for machine learning, batch processing, streaming data, and graph processing. It offers all the essential tools for big data platforms.
Features
- It offers massive speed.
- It has a faster processing time.
- It supports programming languages such as Scala, Java, Python, etc.
- Almost every developer can easily use it.
- It has a unique set of libraries and tools, such as MLib for machine learning, Spark SQL, GraphX, etc.
- Netflix, Airbnb, Uber, and many more reputed companies use it.
3. Google Cloud BigQuery
It doesn’t need an introduction. The platform is a fully managed serverless data warehouse solution for big organizations. The Google Cloud BigQuery has a sturdy and scalable infrastructure to store, query, and determine complex databases.
Features
- It lets users run SQL queries on big data chunks.
- It has impeccable efficiency and speed.
- The platform supports different types of data formats.
- It easily integrates with Google Cloud services.
- Popular companies such as Spotify, Walmart, and the New York Times use it.
4. Cloudera
It is yet another prominent big data platform offering an elaborative list of tools and services to manage and determine big chunks of data effortlessly. Surprisingly, the platform is based on Apache Hadoop.
Features
- It is a hybrid data platform that works across edge and cloud environments.
- It provides a unified platform that easily integrates different parts, including Hadoop Distributed File System, Apache Hive, and Apache Spark.
- It offers advanced analytics tools and machine learning tools to let businesses grow with deep insights and formulate a win-win strategy.
- Prominent companies such as Dell, Comcast, and Nissan Motor
5. Databricks
Last but not least, we have Databricks similar to Apache Spark. The big data platform simplifies data processing and offers a scalable and properly managed infrastructure.
Features
- It lets users easily process big data sets quickly.
- One can perform complex data analytics tasks with its incredible capabilities.
- It offers an interactive and advanced workspace, letting users add codes, visualize data, and do project collaboration.
- Many leading companies, such as Nvidia Corporation, Salesforce, and Johnson & Johnson, use it.
Why Choose NexIT for Big Data Consulting and Other IT Services?
NexIT is a leading and technology-driven IT consulting company where one can find a very wide range of IT products and solutions for all types of businesses. Knowing the rising relevance of data, NexIT offers a wide range of AI-driven big data platform services with the help of an experienced team of AI and machine learning experts.
The brand acts as an IT solutions provider and offers a complete range of IT solutions, including:
- AI big data consulting
- Cloud computing
- Cyber security services
- Nex Gen software development
- Internet of Things services
Along with that, there are many more IT services that NexIT offers at highly competitive rates without sacrificing the quality.
