A Game-Changing Advanced Analytics Solution

A Game-Changing Advanced Analytics Solution

A Game-Changing Advanced Analytics Solution

A Game-Changing Advanced Analytics Solution

On a recent Parker Avery “Talk Retail to Me” podcast episode, Chief Analytics Officer Sam Iosevich discussed Parker Avery’s advanced analytics solution development efforts with the firm’s Director of Solutions Architecture, Leo Greyz. Leo is enhancing Parker Avery’s “Results as a Service” (RaaS) offering and bringing it to the next level as a “Software as a Service” (SaaS) product for retailers and CPG companies.

In this blog post, we provide highlights of their conversation, including Leo’s recommendations for retailers and CPGs who are moving forward with their advanced analytics initiatives.

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Clean Data and External Sources

As analytics grows and initiatives gain momentum, companies will continue to realize that clean data is critical to successful outcomes. Cleansing the data and making sure the hierarchies make sense for the business are also key focus points. Parker Avery has been helping clients achieve this data cleanliness—including data governance—for quite some time.

Bringing in external data sources by leveraging partnerships is also key. This entails combining clean, internal data with external, more predictive data across all retail and consumer brand segments. Knowing the proper data to bring in is highly important to creating meaningful results for analytics initiatives.

Data-Sharing Methods

There are many ways of sharing data, but this could be done easier and more standardized. Some companies are creating different data-sharing approaches, but in the future, they will be more standardized. As a result, data-sharing will be a lot easier to share both internally—between different business functions—and externally with partners, consultants, etc.

Right now, there are different methods, for example, SSTP and Azure, that use data formats such as Parquet and CSV. As such, Parker Avery is approaching development and architecture by having a place to stage the data. But we are also designing the solution to be flexible enough to enable different connectors for different services. As an example, if one client uses Amazon’s S3 buckets, we built the connector that other clients can leverage. If it’s something new, we will build a new connector. Without a standardized approach, multiple connectors are necessary today. If the industry gets to a standardized way of sharing data, we will only need to use specialized connectors for any legacy systems still in use.