# Big Data Needs Even Bigger Protection Author: Pal Sinha, Barnali Author URL: https://financedigest.com/author/pal-sinha-barnali Published: 2017-03-27 Category: TECHNOLOGY Category URL: https://financedigest.com/category/technology Meta Title: Securing Big Data Environments: Challenges and Solutions Meta Description: Learn how to protect your valuable data in big data environments with scalable security solutions, policy-setting challenges, and the need for centralized URL: https://financedigest.com/big-data-needs-even-bigger-protectionhtml ![undefined](https://prod.superblogcdn.com/site_cuid_cm5qst7v3003gwirgwqtxn8i8/images/9057-1-1736844039766-compressed.jpg) _By_ _**Terry Ray**,Chief Product Strategist_ _at_ [_Imperva_](https://www.imperva.com/) With more data being collected by companies than ever before, securing it is no small task.There are many factors that need to be taken into consideration such as; are the environment and the data vulnerable to cyber threats and who has access to the data? And there’s also the issue of compliance. [Big data](https://www.financedigest.com/banks-struggle-to-harness-big-data.html "BANKS STRUGGLE TO HARNESS BIG DATA") deployments are subject to the same compliance mandates and require the same protection against breaches as traditional databases and their associated applications and infrastructure. ![Terry Ray](https://prod.superblogcdn.com/site_cuid_cm5qst7v3003gwirgwqtxn8i8/images/terry-ray-1736844039565-compressed.jpg) Terry Ray Typical security hygiene practices for data security are still applicable for [big](https://www.financedigest.com/avoiding-a-big-data-car-crash-how-to-organise-your-data-to-detect-fraudulent-claims.html "Avoiding a big data car crash: How to organise your data to detect fraudulent claims") data environments. The issue is figuring out how to achieve security and compliance for [big data](https://www.financedigest.com/the-benefits-of-big-data-how-to-convince-your-cfo.html "THE BENEFITS OF BIG DATA – HOW TO CONVINCE YOUR CFO") environments given the unique challenges they present.Much of the challenge of security [big data](https://www.financedigest.com/big-data-analytics-fraud-prevention-in-the-financial-sector.html "BIG DATA, ANALYTICS & FRAUD PREVENTION IN THE FINANCIAL SECTOR") is the nature of the data itself. Enormous volumes of data require [security solutions](https://www.financedigest.com/securing-financial-institutions-with-the-help-of-pam-solutions.html "Securing financial institutions with the help of PAM solutions") built to handle them. This means incredibly scalable solutions that are, at a minimum, an order of magnitude beyond that for traditional data environments. Additionally, your [security solutions must](https://www.financedigest.com/as-saas-grows-financial-services-must-rethink-their-security-approach.html "As SaaS grows, financial services must rethink their security approach") be able to keep up with big data speeds. You’ll need to [focus on data](https://www.financedigest.com/sterling-falls-vs-dollar-as-focus-turns-to-uk-data.html "Sterling falls vs dollar as focus turns to UK data") parsing and collection throughput, the degree of automation that is available, and the ability to deliver real-time visibility of policy violations and other events. [Mixing multiple sources and types of data](https://www.financedigest.com/u-s-yield-curve-inverts-after-strong-jobs-data-world-shares-mixed.html "U.S. yield curve inverts after strong jobs data; world shares mixed") with different access permissions compounds classification and policy-setting challenges, also elevates the need for robust audit capabilities. The multiplicity of big data environments is what makes big data difficult to secure, not necessarily the associated infrastructure and technology. For example, the open source Hadoop framework has different layers of the stack serving a variety of purposes, from distributed storage at the bottom, to table and schema management, distributed programming, and querying/interface options at the middle tiers, and a wide range of [management tools along the top](https://www.financedigest.com/tinnitus-management-market-to-top-us-3-2-bn-driven-by-growing-burden-of-hearing-disorders-fmi.html "Tinnitus Management Market to Top US$ 3.2 Bn Driven by Growing Burden of Hearing Disorders: FMI"). There is no single logical point of entry or resource to guard, but many different ones, each with an independent lifecycle. Often big [data environments will use multiple technologies for data storage](https://www.financedigest.com/data-storage-market-revenue-is-expected-to-increase-at-a-cagr-of-13-6-during-2021-2025.html "Data Storage Market revenue is expected to increase at a CAGR of 13.6% during 2021-2025") and retrieval. For example, it’s not uncommon for an implementation to include either or both relational stores and query tools to support analytical workloads/purposes and non-relational technologies—also known as NoSQL technologies—for real-time, interactive workloads. Many big data environments include [multiple instances or versions of the same core building](https://www.financedigest.com/passive-income-how-to-build-multiple-streams-of-income.html "Passive Income: How to Build Multiple Streams of Income") blocks, except from different vendors, such as different Hadoop distributions and NoSQL offerings. This means a greater amount of diversity and complexity to be addressed by security tools and staff.Big [data deployments typically have a multitude of geographically distributed data stores](https://www.financedigest.com/exclusive-tiktok-nears-deal-with-oracle-to-store-its-data-sources.html "Exclusive-TikTok nears deal with Oracle to store its data-sources") and, therefore, numerous physical nodes requiring protection. This inherently increases the potential for inconsistent security policies and practices, suggesting the need for solutions that feature strong, centralized administration capabilities. There’s also the [challenge presented by the lack of security knowledge and understanding in the people working most closely with the data:](https://www.financedigest.com/financial-services-and-data-how-do-we-meet-the-challenge.html "Financial services and data – how do we meet the challenge?") data scientists and developers. Data scientists, with their skills and experience working with structured and unstructured data to [deliver new insights](https://www.financedigest.com/research-delivers-insight-into-the-global-polymer-surfactants-market-during-the-period-2021-2029.html "Research Delivers Insight Into The Global Polymer Surfactants Market During The Period 2021-2029"), don’t necessarily think about the security of the data. It’s not surprising given that new technologies have encouraged data scientists to view [big data as a giant](https://www.financedigest.com/computer-chip-giant-asml-places-big-bets-on-a-tiny-future.html "Computer chip giant ASML places big bets on a tiny future") sandbox where they are the owners and can decide how the data will be used. While most development projects rely on access to non-sensitive, test data instead of live, production data, big data [application development](https://www.financedigest.com/turbo-compounding-systems-market-development-status-competition-analysis-type-and-application-2026.html "Turbo Compounding Systems Market Development Status, Competition Analysis, Type and Application 2026") by its nature often falls outside of the more secure processes set up within IT. And with higher-access privileges than many others in the organization, developers also present a greater security risk either through accidental means or malicious intent. The number and breadth of data breaches continues to grow unabated, with a 40% increase in data breaches in 2016 reported by the [Identity Theft Resource Center](http://www.idtheftcenter.org/2016databreaches.html).  Therefore, it is crucial that everyone from the CIO on down understands and prioritizes implementing better security for big data—after all, the last thing you want is your company in the headlines for the latest [data breach](https://www.financedigest.com/when-not-if-why-a-data-breach-response-plan-is-more-important-now-than-ever.html "When not if: why a data breach response plan is more important now than ever"). [www.imperva.com](http://www.imperva.com) --- This blog is powered by Superblog. Visit https://superblog.ai to know more. ---