If you’re not experimenting with big data analytics, you could be putting your business at a competitive disadvantage. Analytics projects have the potential to unearth incredible insights related to customers, competitors, markets and internal efficiencies.

However, by gathering more data and opening up more endpoints, organizations create potential vulnerabilities for cybercriminals to exploit. Running headlong into a new data analytics strategy without considering the inherent security challenges at play is a recipe for disaster. But there is a way to balance the security risks with the incredible opportunities that big data analytics present.

Demand for Big Data Analytics Continues Unabated

Interest in data analytics has reached a tipping point, pushing it well beyond the “disruptive technology” phase squarely into a business imperative. In fact, many organizations have moved on to more sophisticated analytical initiatives, including the use of artificial intelligence. According to New Vantage Partners’ “Annual Big Data Executive Survey 2018,” 97 percent of executives were either launching, investing in or building an AI-driven analytics project.

Meanwhile, the pressure’s on for slow adopters to pick up speed. The longer companies wait to deploy big data initiatives of their own, the more they’ll fall behind their forward-thinking competitors. Indeed, businesses that continue to hold off on data analytics risk losing out on a key competitive advantage at this important stage.

Esteemed technology research firm Gartner urged companies to embrace big data as soon as possible.

“As data and analytics become more widely adopted than ever before, the potential for business growth is truly exponential rather than just cumulative,” Gartner’s Rob van der Meulen wrote. “Those who fail to act today will suffer not just in 2017, but also hugely limit their potential for growth in 2018 and beyond, as the returns from increased insight, responsiveness and efficiency snowball.”

Big Data Presents Big Reward, Big Risk

The possibilities presented by big data analytics are incredible, but enthusiasm for this technology should be tempered by the privacy and security concerns at play. Take, for instance, customer engagement projects that involve gathering large quantities of consumer personal information to make brand outreach more targeted. Without high-quality security measures in place, that sensitive information could be at risk for a data breach. Such incidents are typically expensive for organizations once the cumulative costs of remediation, security updates, legal fees and brand reputation loss have all been tallied.

Data security and privacy regulations present additional concerns as organizations must abide by extensive guidelines dictating how information is gathered, handled and stored. The European Union’s forthcoming General Data Protection Regulation, for example, will place strict limitations on what customer data can be collected as well as penalize companies that fail to respond to a breach in a timely manner.

There’s a lot of ground to cover, which is why security conversations should occur at every stage of the big data journey. With the stakes so high, you want to be sure that everything is accounted for.

Adhering to Big Data Security Best Practices

Big data’s greatest asset is also its most worrisome security vulnerability: There’s so much data to safeguard that legacy cybersecurity solutions may not be all to cover it all. As projects scale and data repositories expand, cybersecurity applications struggle to keep up.

Furthermore, data lakes are at risk for tampering and breach since it’s so easy to miss malicious activity hidden within these vast repositories. Any viable big data security solution will need to account for these issues and prevent unauthorized access.

One of the most important features companies should look for in a big data security tool is insider threat detection. These capabilities empower businesses to sniff out suspicious behavior that may indicate the presence of a data breach. Cybercriminals continue to use more sophisticated strategies to avoid detection for as long as possible, so companies should seek out security solutions that are able to identify malicious activity without flagging a bunch of false positives in the process.

In addition, big data repositories should be read-only, meaning only authorized users have the ability to alter stored files and information. Tamper-resistant features further prevent external forces from accessing sensitive data and compromising their integrity.

Successful big data programs depend on a delicate balance of analytics excellence and diligent cybersecurity protocols. High-quality solutions like SenSage AP help lay a sound foundation where security best practices are adhered to and advanced analytics can flourish.

Related Posts

DNN Connect 2022: A trip report

Jul 12, 2022

DNN Connect 2022: A trip report

Brad Mills, Chief Product Officer at IgniteTech, details his experience at the DNN Connect 2022 Conference in Millau, France.

Read more...
The 3 Biggest Developments in Enterprise Cloud Today (and Why They're a Big Deal)

Jul 1, 2022

The 3 Biggest Developments in Enterprise Cloud Today (and Why They're a Big Deal)

Get the top 3 developments in enterprise cloud and see how you can get updates on them for driving intelligent business decisions.

Read more...
3 Things Enterprise Tech Leaders Need To Prioritize in 2022 and Beyond

May 23, 2022

3 Things Enterprise Tech Leaders Need To Prioritize in 2022 and Beyond

To meet succeed in today’s turbulent business environment, enterprise tech leaders need to prioritize 3 things: improving flexibility and agility, institutionalizing cloud cost optimization, and meeting perimeter-less security requirements. Learn why we picked these priorities in this article.

Read more...
How Infobright's Columnar Database Supercharges Decision Making and Supports Organizational Agility

Jul 15, 2019

How Infobright's Columnar Database Supercharges Decision Making and Supports Organizational Agility

Enterprises are moving away from conventional OLTP relational databases in search of more convenient and efficient software tools — that’s where columnar databases come in, demonstrating why Infobright DB remains such a powerful solution for market leaders in these spaces.

Read more...
How an Event Data Warehouse Helps Meet Compliance Demands

Mar 7, 2019

How an Event Data Warehouse Helps Meet Compliance Demands

Event data warehouse solutions are essential to meeting today’s compliance demands, helping businesses land on the right side of data privacy and security regulations.

Read more...
Keep Critical Platforms Online with Database Load Balancing Software

Feb 25, 2019

Keep Critical Platforms Online with Database Load Balancing Software

Companies can avoid costly downtime by implementing database load balancing software and ensuring their business-critical systems stay online and performing at optimal levels at all times.

Read more...