The Weekly Blog is curated content from the Evolytics staff, bringing you the most interesting news in data and analysis from around the web. The Evolytics staff has proven experience and expertise in analytics strategy, tagging implementation, data engineering, and data visualization.

Big Data Tools & Trends

Data Skeptic | Podcast

In this podcast, Microsoft’s CTO for Data discusses the need for enterprise-level businesses to develop a centralized big data architecture that increases efficiencies, improves data security, and becomes a single source for cross-channel insights.

The true potential and power of data is released when you break it out of individual silos, especially for analyzing multi-channel performance.  For example, our Insights Warehouse makes large datasets immediately useful for not just analysts, but also marketers, researchers, product managers, and executives.

Data & Advanced Analytics: High Stakes, High Rewards

Forbes Insights | Whitepaper

When interviewing executives worldwide from various industries, Forbes discovered that, “Over the next two years, more than half of survey respondents plan to invest at least $10 million in data and advanced analytics resources.”

Clear business objectives and sound analytics strategy should drive investment in data and analytics.  If you’re not quite sure where to start though, a data audit is usually a good way to identify opportunities for analytics investment.

How Chief Data Officers Can Get Their Companies to Collect Clean Data

HBR | Article

Bad data costs money. A lot of money. According to this article, analysts can spend 80% of their time in data prep, so they spend only 20% of available time on discovering and communicating insights.  Even scarier is bad data that escapes notice and allows managers to confidently make bad decisions based on bad data.

Companies can safeguard against bad data through a combination of thoughtful process and monitoring tools.  We recommend a tool like Hub’Scan to automate tag testing, monitor for data errors, and ensure data quality.