“ IT ’ S IMPORTANT TO WEIGH THE BENEFITS AGAINST THE COSTS BEFORE IMPLEMENTING MULTIPLE DATA LAKES ”
ENTERPRISE IT
Azure
Synapse Analytics : A Data Lakehouse – James Serra – Triangle SQL Server UG – Aug 2020
is a valuable source for artificial intelligence ( AI ) projects . The large amount of data stored in a data lake can be used to train machine learning models , improving the efficiency of NDT and inspection processes . For instance , historical NDT data and inspection metadata can be used to train machine learning models to predict when equipment is likely to fail , allowing organisations to schedule maintenance and repairs proactively , reducing downtime and increasing the overall efficiency of their operations .
Challenges from setup to data swamps Nevertheless , data lakes have challenges . Complexity in setup and management ,
“ IT ’ S IMPORTANT TO WEIGH THE BENEFITS AGAINST THE COSTS BEFORE IMPLEMENTING MULTIPLE DATA LAKES ”
JAMES SERRA DATA & AI SOLUTION ARCHITECT , MICROSOFT data governance , and security are three such challenges . Additionally , if the data formats vary , these lakes can become a data swamp . Data standardisation is therefore crucial for better data quality , governance , and reusability .
ASTM International recommends using a standardised digital format , Digital Imaging and Communication for Non-Destructive Evaluation ( DICONDE ), to store NDT data and inspection metadata from different NDT methods and sources in a centralised location . DICONDE provides a vendor-independent data storage and transmission protocol for nondestructive materials testing and ensures
116 March 2023