It’s hard to be strategic when you’re fighting fires every minute. Half the respondents to this Digibee survey say they’ve rebuilt six or more key integrations in the past twelve months and 48% say poor integrations have impeded innovation. But just 7% have a data integration strategy in place, even though 57% say it’s a top priority.
Let’s pay some attention to data engineering today, Dear Reader. Observability vendor Monte Carlo Data finds that quality issues impact most or all business decisions at 47% of companies, and 26% of revenue is impacted by poor data quality. The average data engineer spends two days a week dealing with data quality incidents – and 58% say the number of incidents has increased in the past year.
If you think data issues are challenging today, just wait. Ocient finds that mere “big data” is being replaced by “hyperscale data”, which involves higher volumes and near-immediate analytics. Nearly all respondents (97%) expect data volumes to rise quickly in the next few years and 59% expect to move to a new data warehousing platform to handle the growth.
Media mix models (MMM), originally developed in the 1960’s, have undergone a resurgence as new technologies make them easier to execute and click-based attribution becomes less credible. But evaluating MMM brings its own challenges. Australia-based Mutinex offers a vendor-neutral Open Source MMM Validation Framework which is now available for free to North American marketers and agencies.