FAQs

At Switchboard, we imagine the data stack as a wedding cake. The top tier comprises data visualization dashboards (Tableau, Looker, Power BI etc), as well as custom applications and data science projects.

The second tier typically comprises the data lake (or warehouse), which stores the data. These are increasingly cloud-based, such as Snowflake, BigQuery, AWS or Redshift, although customers also use storage facilities such as GCS buckets with Parquet files; HDFS (Hadoop Distributed File System); or SFTP.

The third tier — where the Switchboard application sits — is what many of our customers call the ‘partner ecosystem' or ‘data ecosystem'. We call it the Data Operations (DataOps) layer — the single pane of glass that sits on top of a messy ecosystem of third-party data, APIs, JSON objects, CSVs, databases, or email. Switchboard's cloud-hosted platform provides a consistent and repeatable set of workflows and processes to bring together all this data through default standard connectors, aggregate and normalize it using a transparent technology and workflow, and load it into the EDW.

At Switchboard, we imagine the data stack as a wedding cake. The top tier comprises data visualization dashboards (Tableau, Looker, Power BI etc), as well as custom applications and data science projects.

The second tier typically comprises the data lake (or warehouse), which stores the data. These are increasingly cloud-based, such as Snowflake, BigQuery, AWS or Redshift, although customers also use storage facilities such as GCS buckets with Parquet files; HDFS (Hadoop Distributed File System); or SFTP.

The third tier — where the Switchboard application sits — is what many of our customers call the 'partner ecosystem' or 'data ecosystem'. We call it the Data Operations (DataOps) layer — the single pane of glass that sits on top of a messy ecosystem of third-party data, APIs, JSON objects, CSVs, databases, or email. Switchboard's cloud-hosted platform provides a consistent and repeatable set of workflows and processes to bring together all this data through default standard connectors, aggregate and normalize it using a transparent technology and workflow, and load it into the EDW.

At Switchboard, we imagine the data stack as a wedding cake. The top tier comprises data visualization dashboards (Tableau, Looker, Power BI etc), as well as custom applications and data science projects.

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As a corporate enterprise, we're used to pulling and aggregating terabytes of data each day via a host of platforms into Google Cloud. We've built our own infrastructure to do this. Where would Switchboard sit within our data stack?

We need to analyze data from a host of marketing platforms. How does Switchboard pull the raw data from each source, and how often?

We've already built the DataOps infrastructure in-house to pull the data from the source (e.g., Google's API), log and monitor it. So, what are the advantages of using Switchboard on top of these capabilities?

In the past, we've lost temporary access to platforms such as Facebook because they've implemented changes which require an app review. Does Switchboard handle security reviews and access reviews for us?

Can Switchboard combine metrics — for example line items and orders — so that we don't have to process them as separate queries?

And if multiple teams access the data and make changes, can we see who and when?

As a corporate enterprise, we're used to pulling and aggregating terabytes of data each day via a host of platforms into Google Cloud. We've built our own infrastructure to do this. Where would Switchboard sit within our data stack?

We need to analyze data from a host of marketing platforms. How does Switchboard pull the raw data from each source, and how often?

What type of data sets does Switchboard handle?

Our business teams use a variety of applications to share data. What formats can Switchboard export normalized data in?

Google keeps refreshing its data at different timepoints. How can Switchboard help us retrieve the right data at any given point in time?

When there are restrictions on the metrics you can pull and combine (for instance, in GCM, you cannot always combine all the metrics you want to), does Switchboard alert us?

When our business teams access the data and choose their reporting metrics — for example date, site, advertiser — are all these metrics version controlled?

If changing our metrics affects previous periods of data, how do we apply these changes retrospectively?

What type of data sets does Switchboard handle?

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