data management
Exago on FHIR
The healthcare industry is on FHIR. Or, it will be soon. FHIR (pronounced “fire”) protocol is the future of health data interoperability. Some in the healthcare IT industry have even claimed that FHIR “has the potential to be as ubiquitous and useful as the internet itself.” For those unfamiliar with FHIR protocol, it isn’t a…
The Role of BI in Precision Medicine
For many, precision medicine calls to mind cutting-edge technologies like genomic sequencing, machine learning, and artificial intelligence: ultra-high tech for ultra-keen diagnoses. These aspirational technologies are poised to play a crucial role in modern healthcare, but their impact is precluded by logistical problems around data generation, storage, and transmission. The Precision Medicine Initiative (PMI) calls…
Think Outside the Cube
These days, most SaaS providers embedding BI in their applications recognize they also need some kind of ETL. (Check out this infographic if you aren’t sure what ETL is). In response, many BI platforms are coming up with their own proprietary data preparation solutions. Some have chosen to use multidimensional databases, often referred to as…
Using BI to Audit Data Quality
Data Talks, Episode 15 Data Talks is Exago’s podcast on all-things business intelligence, analytics, and application software. When most people think of BI, they think about extracting insights from their data, not about their data. This month, George Firican explains why BI can be a surprisingly effective tool in data quality auditing — particularly for…
Assessing Data Veracity
There are different takes on what veracity refers to, but the overall consensus is that data veracity reflects the truthfulness of a data set and your level of confidence or trust in it. I’ll take this a step further and say that data veracity is your level of confidence/trust in the data based on its…
18 Data Quality Issue Attributes You Should Be Logging
If you’ve already started or are planning to start a data governance program to support your data quality improvement goals, you need a structured way of tracking your data quality issues and their status. There are different ways of doing this, of course, with either the help of dedicated data quality tools, incident management and ticketing…
How to Not Get Overrun by Your Data Overrides
Large-scale enterprises rely heavily on market and consumer data sourced from outside vendors, but that information comes at a cost. In addition to intermittent issues with the data quality itself, consumers of vendor data can face timeliness problems, non-standard formats, coverage gaps, and lags in technical support. Despite these and other issues, vendor data can be…
Infographic: How ETL Primes Your Data For Reporting
There’s a lot your BI solution can do to make reporting off live data faster and more efficient; but when you’re looking for an even more substantial performance boost, it’s time to bring out the big guns. Any pre-processing you do to your data is work your system can skip when actually executing a report, bringing…
Evolution, Not Revolution: Tips for Transitioning to a Federated Database System
As enterprises scale, they develop data inefficiencies. Sometimes these inefficiencies arise internally, between departments or branches, while others emerge as the parent company acquires smaller companies, each with their own databases and IT departments. In either case, communication issues ensue as siloed databases and IT redundancies begin costing the enterprise non-trivial sums of money over…
The Emergence of the Chief Data Officer
Above: Popularity of “Chief Data Officer” searches (blue) compared to “Chief Technology Officer” searches (red) and “Chief Information Officer” searches (yellow) from Jan 2004 through present according to Google Trends. The period with the most searches is given a y value of 100, and all other periods are charted in comparison to that peak. What […]