Here in Colorado, it’s just about winter sports season. And that means I’m thinking about making the drive up to Summit County to take advantage of some of best skiing anywhere. The destination is completely worth it, but the road is not without its potential risks: slippery inclines, dramatic switchbacks, snow drifts and 18-wheelers barreling through the weather toward the West Coast.
Businesses today face a similar situation: the ability to use data to gather insights across the enterprise is an exhilarating goal, even though getting there can require overcoming some hazards. Many enterprises are moving company information into cloud data platforms like Snowflake in big data analytics projects that take advantage of scalable storage, accessible compute power, and integrations with cloud-based BI tools for a sophisticated view of every part of the business. To get the full picture though, sensitive data must often be included. Whether that’s personal customer data or highly restricted business information, uploading and utilizing that sensitive data creates a risk due to privacy regulations and confidentiality concerns.
But just like the drive up the mountain, there are technologies that can make it easier and safer for companies to make the journey. Here are three examples where ALTR’s technology can help companies reach their big data analytics goals:
Big Data Analytics Insight #1: Determine the real cost to serve customers
The CFO of a logistics company wants to determine the actual costs to serve their customers in order to better align pricing and improve margins. They pull operational data, inventory management, warehousing, and fuel and vehicle maintenance costs into Snowflake. But this doesn't provide a full picture without including the costs of the people doing the work. The last key piece of data is compensation information for each employee involved in delivering the products. However, unlike the other information, this is highly sensitive information about what each individual employee gets paid along with their banking info. Putting it into Snowflake means that it could be accessible to some employees outside the finance and HR teams, like the Snowflake admin, for example.
ALTR automates and makes the handling of this data easy, and because ALTR sits outside Snowflake, we’re able to create a secure mechanism that delivers an alert every time that sensitive data is accessed – by anyone. The logistics company is able to utilize all the required information – even private payroll data – to accomplish their big data analytics goal.
Big Data Analytics Insight #2: Better model customer buying behavior to boost sales
The CMO of a consumer goods company wants to get a holistic view of its customers and their buying behavior, but data is spread across multiple on-premises and cloud-based systems: Salesforce, Marketo, eCommerce sites, backend ERP systems, and customer behavior analytics tools. In order to tie demographic information about specific buyers to their online activity and buying activity, the data all needs to be in one place with at least one common value, usually a piece of PII (name, email, SS#). With this, marketing teams can look for buying indicators in localized regions: perhaps a mom looked at a specific blog post before purchasing diapers in Austin, TX. Maybe that’s a pattern: several moms looked at that post before buying diapers in Austin. Then marketing can use that insight to promote that blog to other moms in Austin, to drive similar purchases.
ALTR allows companies to protect sensitive PII data easily in Snowflake. You can find and classify personal information, see how it’s being used, then set policies to control access and limit consumption in the event of a policy infringement. Marketing teams can safely (and in compliance with privacy regulations) use sensitive data to do multivariate analysis, create an accurate model of customer behavior, and uncover opportunities to grow sales.
Big Data Analytics Insight #3: Discover ways to optimize specific sales territories or business units
As the value of data analytics has grown, the number of people across the business who have or want access has grown in tandem. It’s no longer a handful of data engineers or analysts who can peer deep into every corner of the business but everyone from marketing to finance to HR to engineering to sales who wants to access operational, sales, marketing or finance data to make better decisions. A sales manager may want to get a better view into her territory – looking at past sales and annual trends or hot industries to find opportunities for the next quarter. All of the data to drive these insights will have to be consolidated into a single repository like Snowflake for cross reference, along with the same data for every other sales territory. In order to make her territory data available to that sales manager, the other territory data must be made unavailable so that it stays confidential.
ALTR enables companies to easily set access policies based on role for any data deemed sensitive or confidential. That means your database admin can ensure each sales manager – or any other role in the company – only has visibility into the information they need to do their jobs better. The ability to easily control access means data can be made more freely available.
This Big Data Analytics Journey is All About the Destination
Think of ALTR as a set of snow tires you put on at the beginning of the season, as you head into sensitive data territory. They’re easy to install and equipped to help you make the journey up the mountain whenever you’re ready to go. And the best part is that once you have them, you can stop thinking about the risks and concentrate on the amazing view.
