New Big Data Products Comparison

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New Big Data Products Comparison

On February 28, 2017, Posted by , in Big Data News, tags , , , , With Comments Off on New Big Data Products Comparison

Big data can be overwhelming. You need to have good quality software to analyze these voluminous data sets. The fact that a normal database or spreadsheet application will have a hard time processing millions of data, companies are purchasing data analytics software to help them with the job.

Ever since businesses started using big data, software companies started developing their data analytics software and mobile big data. All of them focus on one thing, to help the users uncover the gem of information buried in the pile of datasets from different sources. Analytics software in the market today can gather, analyze, process, and give you almost instantaneous results.

Tips on How to Choose Big Data Products

It might be confusing sometimes, that due to the ubiquity of analytic software available in the market today, to select the best software for your company – whether for an established or for a startup one.

You need to consider the software features such as modeling techniques; integration and accessibility, connectivity, flexibility in deployment in choosing the best analytics software for your business. It would be best for you to consult with data experts before you purchase software for your big data projects.

Below is the list of data analytics software used for big data processing that is available in the market today. We have included their pros and cons that will hopefully assist you in deciding which one to purchase.

  • Sisense

Pros: It offers both on premise and cloud-based options for users. It also works really well with large data sets and comes with Elasticube feature that allows users to take data snapshots.

Cons: The Elasticube is not very user-friendly. It requires technical expertise for this to be done. Its dashboard also only interacts on the web.

  • IBM SPSS

Pros: Very user-friendly software developed by IBM. It also has the Ability to run additional analyses which are not built or sold together with the product.

Cons: Data manipulation is not as easy as doing it in Excel. Data visualizations are also very limited such as creating graphs for presentation. With larger datasets, sometimes, the software freezes.

  • SAP HANA

Pros: IT offers transactional data analytics in real time. It offers many features such as simplified DBA experience. It is highly integrated and verified by SAP, especially when using SAP applications.

Cons: Cost for both hardware and software license is quite higher than others.

  • Teradata

Pros: One of the major reasons why many businesses use this is its speed and performance. With Teradata, large scale and long running reports can be completed in a little over an hour.

Cons: Performance of workload can decrease.

  • Knime

Pros: It reads data from multiple sources. It has a very simple and user-friendly UI.

Cons: Beginners need to spend more time using and studying it before they can appreciate the full potential of the software.

Common Misconceptions with Big Data Analytics

Some people though that big data services companies and analytics can solve all of their problems. It’s a lie. They get too excited about being a step ahead of their rivals that they collect loads of data but do not know how to make sense of them. We must all understand that data in its raw form, no matter how much you have them, without thorough analysis, is useless.

It is best to consult experts in big data analytics first before deploying any platforms or software. Read and research about the products available and try them out.

Learn what analytics software is available for you to download for your big data analytics!

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