How Hadoop Analytics Better Fulfills New-Age Business Owners Big Data Business Needs?

The modern day ultra-connected world is generating huge volumes of data quickly. This makes big data analytics an important tool for business enterprises looking to leverage their data for better informed decision making.

In the midst of this entire big data revolution, Hadoop analytics has been heavily encouraged and adored as a big data storage and analytics platform that delivers one-size-fits-all solution for the new-age business enterprises. While Hadoop has garnered a lot of hype, there are few situations wherein running workloads on a traditional database might even work.

For business enterprises evaluating, which functionality would better serve their big data use requirements, let us read on and understand few key questions to be asked while choosing the best Hadoop databases.

Hadoop is an open source software framework, which is particularly built to deal with huge volumes of structure and semi-structured data. Companies that are considering Hadoop adoption must calculate whether their existing or future big data needs require the kind of facilities that Hadoop offers.

Hadoop Analytics: Whether Big Data Is Analyzed Structured Or Unstructured?

•  Structured Data: The data which exists in the fixed parameters and fields of a record or file is known as the structured data. Considering the fact that the structured data even in huge volumes can be stored, queried, and analyzed in an easy manner, this kind of data is best served through a traditional database.

• Unstructured Data: Data which comes from different sources like videos, emails, audio files, text documents, photos and social media posts is known as the unstructured data. The unstructured data is complex and voluminous thus, it cannot be efficiently queried through a traditional database. Hadoop analytics has the ability to join, accumulate and analyze huge stores of multi-source data without structuring it first enables companies to gain deeper insights speedily. Hence, Hadoop is just perfect for business enterprises that are looking to store, handle and analyze huge volumes of unstructured data.

Why A Scalable Big Data Analytics Infrastructure Has Become a Must-Have for Companies?

Business enterprises that are challenged through amplifying data needs will require taking benefits from Hadoop analytics’ scalable infrastructure. Scalability enables the Hadoop BI tools servers to be added whenever required to accommodate the speedily increasing workloads. Hadoop being a cloud-based service provides more flexible scalability to companies through spinning virtual servers up or down in just few minutes to properly accommodate the changeable workloads.

How Much Cost-Effective is Implementing and Using a Hadoop Database for Business Enterprises?

Cost-effectiveness has always been a major concern for new-age businesses looking to adopt the latest technologies. While considering Hadoop BI tools usage and implementation, business enterprises require doing their homework for ensuring that the realized advantages of a Hadoop deployment compensate the costs for fulfilling your company’s data storage and analytics needs.

All said and done, Hadoop has numerous things going for it, which makes the implementation extremely cost-effective than businesses might realize. Hadoop BI tools saves money through blending open source software along with the commodity servers. Cloud-based Hadoop platforms trims down the costs further through eliminating the outlays of physical servers and warehouse space.

Hybrid systems that incorporate the Hadoop analytics platforms with the traditional relational databases, are garnering huge popularity for providing a cost-effective approach for companies to leverage the perks of both platforms.

Hadoop Analytics: Whether Quick Big Data Analysis Is Important Or Not?

Hadoop BI tools are designed for huge distributed data processing, which addresses each file in the database and this takes a lot of time. For tasks wherein quick performance is not critical like running end-of-day reports to reviewing every day transactions, scrutinizing historical data and performing analytics in which a slower time-to-insight is up-to-standard, Hadoop is just perfect.

Where business enterprises depend on time-sensitive data analysis, a traditional database is an ideal fit, as shorter time insight is not really about analyzing huge unstructured datasets, which Hadoop analytics does perfectly. It is all about analyzing lesser data sets in real-time that is what Hadoop databases are equipped to handle well.

While the major perks of big data analytics in delivering deeper insights which lead to competitive benefits are real, those benefits can only be availed through business enterprises which exercise due diligence in ensuring that Hadoop analytics tool best serves their requirements.