Retail-Ready Data Lake as a Service for All Analytics
Industry: Retailers & Restaurants
Retail Analytics Use Cases:
- BI/Analytics for SaaS, POS, ERP, etc.
- Analytics for eComm/Web (Omniture)
- Customer Loyalty, C360
- Marketing Analytics
- Offer, Pricing and Planning
- Facilities and Operations
- IOT/Beacon Pilots
Contact Cazena to learn more about our experience with retailers and restaurants.
Accelerating Analytics from Customers to Marketing, Supply Chain and Beyond…
Cazena has worked with many types of retailers: brick-and-mortar, e-commerce and national restaurant chains. The Data Lake as a Service increases capabilities overnight, with no work required by IT teams. Cazena’s SaaS experience means the data lake is always simple, automated and supported.
For retailers and restaurants, a Cazena Data Lake as a Service has meant:
- Giving a data science team the cloud power they needed to develop a new forecasting algorithm, with a multi-million dollar impact
- Migrating an aging on-premises data warehouse and BI application to AWS Redshift in 4 weeks, reducing IT admin time and costs
- Launching a complete data lake and advanced analytics program in under a week with no IT impact or support required
We know that retailers face a unique time, with an endless amount of data, many new ideas and serious competitive pressures. That’s why teams turn to Cazena to scale to the next-generation of cloud analytics flexibly, with automation. Cazena’s Data Lake as a Service empowers retail teams to focus on accelerating outcomes and making an impact faster.
Cazena is my data lake team. There are more strategic things we need to do with our time.”
Cazena has proven experience overcoming the hurdles that prevent retailers from becoming data-driven. Common challenges faced by Cazena customers in retail:
- Need to manage a wide variety of SaaS and analytics datasets. Data formats are proliferating, introducing challenges for retailers with limited systems and storage. Data is often siloed in different locations and systems, from the cloud to storefronts to datacenters. Cazena has successfully connected to a huge variety of retail data sources, and can store all of that data cost-effectively. Cazena cloud data lakes can leverage object storage, such as S3 on AWS. Security is built-in, along with encryption and compression.
- Need support for All Analytics, not just SQL. Many retailers know SQL data warehousing, but don’t have the skills for production-grade Hadoop and Spark in a public cloud infrastructure. Worse, those skills can be difficult to hire and retain. Cazena’s Data Lake as a Service supports All Analytics, on delivery, including R, Python, Java, Scala, ML/AI and more. Data lakes are continuously optimized to support the current mix of analytics workloads. Instantly expand capabilities without having to learn new skills.
- Need cloud power for game-changing advanced methods. Today’s advanced analytics are not all about large data volumes. Cloud scale is also required to handle today’s data variety, and complexity in model simulation, algorithm development and cutting edge ML/AI techniques. Data science and innovation teams need data lakes that are optimized for new tools and techniques.
Cazena resolves all of these challenges and more, with the first Data Lake delivered as SaaS. Everything is included. Everything is supported. Each data lake is private and single-tenant in the cloud, configured for the needs of each enterprise client. The solutions mentioned in this section have used technology from these partners and others.
How Cazena’s Data Lake as a Service has accelerated outcomes for retailers and restaurants:
- SaaS-Style Data Lake Enabled Fast Launch for Lean IT Team. A Cazena Data Lake as a Service turned out to be a silver bullet for the IT Director at a new national restaurant chain. The startup had one overworked staffer responsible for all applications and analytics. Cazena solved many problems at once, guaranteed security and meant a lot less things to worry about. The Data Lake as a Service was live in a day, securely collecting and storing POS, SaaS and ERP data from a variety of other SaaS applications. Then, analysts from sales, marketing and operational teams use Tableau, Spotfire or SQL to develop reports and dashboards. Soon, data scientists also started using the data lake for advanced analytics (R, Python) for marketing, offering pricing and inventory forecasting / planning.
- Accelerated Development of a New Forecasting Algorithm. Data science sometimes requires compute power to process through complex models and simulations. In one case, it didn’t take long after Cazena’s introduction for the team to start testing a new algorithm they’d been wanting to try (but hadn’t had the infrastructure). Within weeks results looked promising, and within a few months, the team could confidently predict that the new forecasting related algorithms could potentially save multiple millions.
- EDW Cloud Migration in weeks, plus reduction in TCO. Cazena completed a lift-and-shift cloud migration in weeks, moving an aging data warehouse to AWS. With Cazena, migrations are seamless, ending in a SaaS experience that delivers up-to-date capabilities automatically, with no burden on IT.