Elephant_1f22d2_1180744

Hadoop Security Issues and Best Practices

Hadoop Security Issues and Best Practices

The big data blast has given rise to a host of information technology software and tools and abilities that enable companies to manage, capture, and analyze large data sets of unstructured and structure data for result oriented insights and competitive success. But with this latest technology comes the challenge of keeping confidential information secure and private.

Big data that resides within a Hadoop environment contains sensitive confidential data such as bank account details financial information in the form credit card, corporate business, property information, personal confidential information, security information of clients and all.

Due to the confidential nature of all of data and the losses that can be done should it fall into the wrong hands, it is mandatory that it be protected from unauthorized access.

look at some general Hadoop security issues along with best practices to keep sensitive data protected and secure.

It wasn’t all that long ago that Hadoop in the enterprise was primarily deployed on-premise. As such, informative confidential data was safely confined in isolated clusters or data silos where security wasn’t a problem. But that fastly changed as Hadoop developed into Big Data as-a-Service (BDaaS), took to the cloud, and became surrounded by an ever-growing ecosystem of softwares and applications. And while these innovations have served to democratize data and bring Hadoop into the mainstream, they have also created new security concerns for organizations that now struggle to scale security in step with Hadoop’s rapid technological advances.

Read Also:
Splunk adds machine learning that's both easy and open

For many companies Hadoop has developed into an enterprise data platform. That poses new security challenges as data that was once siloed is brought together in a vast data lake and made accessible to a variety of users across the organization. Among these challenges are:

Clearly, today’s compnies face formidable security challenges. And the stakes regarding data security are being raised ever higher as sensitive healthcare data, personal retail customer data, smart phone data, and social media and sentiment data become more and more a part of the big data mix. It’s time for companies to reevaluate the protection and safety of their data in Hadoop and to reacquaint themselves with the below Hadoop security good practices.

1. Plan before you deploy – Big data protection strategies must be determined during the planning phase of the Hadoop deployment. Before moving any data into Hadoop it’s important to identify any confidential data elements, along with where those elements will reside in the hadoop system.

Read Also:
Build Insight-Driven Advantage With Analytics

 



Enterprise Data World 2017

2
Apr
2017
Enterprise Data World 2017

$200 off with code 7WDATA

Read Also:
Keys to Working With Big Data

Data Visualisation Summit San Francisco

19
Apr
2017
Data Visualisation Summit San Francisco

$200 off with code DATA200

Read Also:
Boost Your Analytics: The Rise of the Citizen Data Scientist

Chief Analytics Officer Europe

25
Apr
2017
Chief Analytics Officer Europe

15% off with code 7WDCAO17

Read Also:
The future of oil & gas industry – big data or die!

Chief Analytics Officer Spring 2017

2
May
2017
Chief Analytics Officer Spring 2017

15% off with code MP15

Read Also:
6 Artificial Intelligence developments revolutionizing health care

Big Data and Analytics for Healthcare Philadelphia

17
May
2017
Big Data and Analytics for Healthcare Philadelphia

$200 off with code DATA200

Read Also:
The Future is What Happens When People Embrace Open Data

Leave a Reply

Your email address will not be published. Required fields are marked *