Big Data As A Service: Your Complete Guide In 2021

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The world revolves around digital technology nowadays, especially with the rise of computers, mobile devices, and big data. There are tons of information being generated, processed, accessed, and analysed every second, owing to the automation and artificial intelligence of various software programs and applications.

Both private individuals and businesses benefit from manual to automated solutions and the evolution of printed texts to virtual or web-based resources, transforming day-to-day lives and operations. All of these things are made possible with big data as a service.

In this article guide, you’ll learn more about big data as a service for your detailed references.

What Is Big Data?​

As the term implies, big data involves huge amounts of details, processes, or information humans won’t be able to comprehend as only advanced data processing software could do so. Big data consists of massive complex structured datasets (e.g., numbers and texts) and unstructured data sets (e.g., video, audio, image files, log files, and social media posts) not fitting in spreadsheets. Also, big data rapidly generates and transmits to various sources.

Understand big data by checking its following qualities:

Enormous​

Are you familiar with megabytes and gigabytes of the data storage capacity of smartphones and computers? With big data, the volume of data is gigantic, in which the data is measured in petabytes (1 petabyte is 1024 terabytes) and zettabytes (a trillion gigabytes or a billion terabytes).

Fast​

The velocity or speed in analysing big data is lightning fast, allowing real-time processing. Thus, it helps in quick but sound decision-making to keep up with the tight competition, most especially in the business sector.

Varying​

Videos, texts, graphs, emails, audio files, and scientific data make up a big data stream. Each data has its own unique, varying qualities.

Importance Of Modern Big Data Tools​

Modern advanced tools can help sort, access, and process big data to make them easily accessible, faster to interpret, and readily available in desired formats. For instance, a news aggregator or a content aggregator pulls together apps and web content such as newsletters, blogs, and social media posts from various online sources for resale or reuse as a way of curating content.

Examples Of Big Data​

One good example to find big data is the Internet. Every day, millions of web content are being uploaded online. People shop, pay bills, do business, chat, and call using the Internet. Just imagine the bulk of data being fed and retrieved online with millions of users worldwide.

Big data isn’t just the information you see online. It also includes car computer data to show a driver’s driving habits and gearbox settings, the data on wearable devices like smartwatches, home security systems, and others.

Here are some other examples of big data:

  • Social media sites
  • Credit card information
  • Shopping sites
  • Online courses
  • Electronic medical records
  • Health device sensors
  • Telecommunication devices
  • Manufacturing equipment sensors
  • Automated Teller Machines (ATMs)

Big Data As A Service​

You’ve learned about big data, so what’s big data as a service (BDaaS)? Big data as a service refers to the combination of big data technologies and cloud computing platforms, reducing the cost and time needed in big data project deployment. It enables businesses to manage a high volume of data on cloud platforms, providing easy accessibility.

Here are the two key players in big data as a service:

1. Cloud Computing Platforms

Cloud computing refers to the delivery of databases, storage, servers, analytics, intelligence, software, and other computing services over the Internet. Cloud computing has three layers or main service models in which big data as a service also carry, including the following:

  • Infrastructure as a Service (IaaS)
This common cloud computing service model provides the fundamental infrastructure of data storage drives, virtual servers, operating systems, and networks. IaaS removes the hardware aspect, providing reliable, scalable, and flexible business operations.

  • Platform as a Service (PaaS)
With PaaS, cloud computing providers establish the software and infrastructure framework through web applications. Multiple web developers usually need to work on a single project.

  • Software as a Service (SaaS)
SaaS deploys software over the internet to businesses willing to pay through a pay-per-use or subscription model.

2. Big Data Technologies

Data management for big data involves using leading-edge technologies to be able to access, handle, store, process, and analyse complex data.

Here are some of the big data technologies commonly used nowadays:

  • Artificial Intelligence (AI)
AI refers to designing smart machines to accomplish tasks usually demanding human intelligence. Some examples of AI include Siri, Alexa, Cortana, and other AI assistants and devices such as smart TVs, speakers, and self-driving vehicles. Artificial intelligence allows systems to make decisions and actions, greatly benefiting various industries.

  • Predictive Analytics
It aims to forecast future events using previous data through data mining, statistical modelling, and machine learning technologies. The predictive analysis applies to predicting consumer needs, stock exchange, and real estate market trends.

  • NoSQL Database
This big data technology designs modern applications using a vast range of database technologies, gathering and retrieving data. NoSQL database stores unstructured data, offers flexibility, and delivers fast performance when dealing with varying big-scale data types. Also, NoSQL promotes ease of control, device scaling, design integrity, and quick calculations.

  • Blockchain
It carries Bitcoin, a digital currency having a unique secured data feature unable to be modified or deleted later on. Blockchain is a secure ecosystem of big data technology, embraced by financial institutions, retailers, insurance companies, and the healthcare sector.

Types Of Big Data As A Service​

BDaaS technology offers a highly functional architecture, including big data storage infrastructure, big data processing modules, and impressive analytical tools, reducing expenditures on hiring data scientists and programming experts.

Generally, BDaaS consists of two things, which include a service-oriented data architecture and cloud virtualization. Here are the major types of BDaaS:

  • Core BDaaS
This generic BDaaS implements using minimal platforms, which is commonly used in the as-a-service domain. Companies can use core BDaaS to help maintain inconsistent workloads. Core BDaaS has a basic infrastructure and storage applications like NoSQL processing engines.

  • Performance BDaaS
Performance BDaaS is a database ecosystem with optimized infrastructure and provisionary usage of other hardware and software services to maximize performance, increasing computing potential and scalability at predictable costs.

  • Feature BDaaS
It’s a feature-driven BDaaS focusing on efficiency and abstraction, familiarizing users with big data. With feature BDaaS, the BDaaS provider’s services usually include a web and programming interface, along with services reaching the SaaS layer.

Feature BDaaS has evolved to provide application possibilities depending on specific assignments. The basic infrastructure employs different basic software features with storage and computing independent of the BDaaS service provider, promoting full scalability.

  • Integrated BDaaS
Integrated BDaaS can be fully and vertically integrated, featuring the benefits of both performance BDaaS and feature BDaaS. This fully integrated BDaaS promotes greater productivity, supporting users, experts, and other business stakeholders to deliver maximum performance.

Benefits Of Using Big Data As A Service​


Businesses worldwide are struggling with data storage, and handling a high volume of data has become challenging to process and obtain invaluable results. Big data as a service is designed to solve all these issues, equipped with advanced statistical analytical tools, allowing users to quickly access and analyse complex data sets for smart decision-making. BDaaS provides data analytics combined with customized storage, hardware, and software.

The benefits of big data as a service are as follows:

  • Great Cloud Storage
Companies don’t need to rely on hard drives, external drives, and other forms of physical data storage or hardware to keep tons of data. Big data as a service utilizes cloud storage solutions for easy data storage, retrieval, and backup.

Businesses can benefit from cloud storage, especially in implementing a marketing campaign. For instance, publishers and marketers can monitor a large web content campaign or search engine optimization (SEO) campaign to reach a huge audience using BDaaS. Also, creating, curating, and publishing content is a lot faster and easier with the help of BDaaS.

  • Cost-Effective
Any type of business can greatly benefit from BDaaS cost-wise. Installing an in-house big data infrastructure can be expensive, and businesses can seek the professional services of BDaaS companies to save money, suitable for small and medium-sized enterprises.

By working with a BDaaS provider, users only pay for the services they use. As compared with the cost reduction of training employees in terms of data processing, BDaaS is a more cost-effective solution.

  • Straightforward
BDaaS is a simple and efficient way to manage big data from any enterprise’s division. Users can manipulate data and make room for drastic data structure changes.

BDaaS utilizes application software for a wide range of big data services such as straightforward reporting, querying, data mining, and analytical processing, transforming raw data into constructive data for business intelligence, increasing actual business efficiency.

  • Scalable
Businesses adopt BDaaS to earn a competitive advantage in which data management and scalability are crucial to attaining a steady stream of good profits. With higher volume, enterprises need to gather more data, thus requiring bigger storage.

With BDaas, businesses won’t run out of storage because it’s designed to store tons of information. BDaas service providers give additional storage at an extra charge, covering the cost of upgrading storage capacity and technology required by the company. It’s still a more cost-effective storage solution than continuously adding in-house hardware.

  • Promotes Business Growth
One of the key ingredients of BDaaS is complex event-driven processing, enabling data management in explanatory, predictive, and descriptive modules to be interpreted accurately. Users can get valuable information through different analytical approaches when handling threats, possibilities, and opportunities toward overall business growth. BDaaS implements real-time processing techniques with on-demand features, which is timely and less costly.

  • Additional Layer Of Security
Big data is controlled by the BDaaS provider, giving an additional layer of security to make data processing highly secure. However, the use of BDaaS raises concern because it means entrusting your big data to a third-party controller, which holds true when using other software and technology.


Choosing the right BDaaS provider and investing in data security can greatly benefit companies. The use of BDaaS for big data storage, access, processing, and analysis remains the best option when handling such information.

How To Choose A BDaaS Provider​

Every business owner must be keen on selecting the right provider when embracing big data as a service to realize overall goals. For one, companies should hire BDaaS experts who use the right big data technologies to promote superior data security.

When choosing a BDaaS provider for your business, it’s crucial to consider the following:

  • Start-up Costs
Many BDaaS providers offer a free trial, allowing you to see the results before committing and spending money.

  • Scalability
Using hybrid cloud systems is one of the trends in big data. Choose a capable BDaaS provider to provide scalable solutions. Big data tend to grow in size quickly, so you need to pick a scalable service, which is also affordable and reliable in processing resources when the need arises.

  • Business Niche
Find a BDaaS provider supporting your customers and your business. Look for a BDaaS service provider giving project planning support, consulting, analytics, and data hosting. BdaaS is suited to strategies involving large data analysis, especially unstructured datasets. Remember, there’s a requirement to move huge amounts of data to a third-party provider, so choose one with fewer security and compliance problems.

  • Feedback And Real-time Analysis
Successful big data projects offer insights depending on the present situation, so actions can be taken in real-time.

  • Managed And Self-service
Most BDaaS provide a combination of both approaches. Technical staff members work behind the scenes, providing you with transparent services.

Conclusion​

You’ve just learned the basics about big data, and this complete guide shows how big data as a service helps manage, store, and analyse tons of data over the web and computer systems in various devices, tools, equipment, and operating systems.

With BDaas, companies can carry out various business processes such as sales and marketing, customer service, accounting, and others quickly, easily, and accurately. Indeed, the role of BDaas in today’s fast-paced modern era can’t be discounted, transforming businesses and economies.
 
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