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Data Lakes: A Panacea for Big Data Problems, Cyber Safety Issues, and Enterprise Security
Published in Mohiuddin Ahmed, Nour Moustafa, Abu Barkat, Paul Haskell-Dowland, Next-Generation Enterprise Security and Governance, 2022
A. N. M. Bazlur Rashid, Mohiuddin Ahmed, Abu Barkat Ullah
Classical data query languages, such as SQL for relational databases, XQuery for XML databases, JSONiq for MongoDB, or SPARSQL for RDF, can be used for data access in a data lake. However, because of storing heterogeneous data in a data lake, a simultaneous query cannot be performed in the heterogeneous databases using the above query languages. Query techniques, such as Spark SQL and SQL++ from multistore, can be used for querying relational databases and semi-structured data in JSON format. Scalable query rewriting engine (SQRE), CloudMdsQL, Apache Phoenix, and Apache Drill are other query languages that can be used for data access in the heterogeneous data lake. For business users, interactive and user-friendly tools, such as Microsoft Power B.I. and Tableau, are also used for data reporting and visualization tasks over data lakes.
Data-driven machine criticality assessment – maintenance decision support for increased productivity
Published in Production Planning & Control, 2022
Maheshwaran Gopalakrishnan, Mukund Subramaniyan, Anders Skoogh
Out of the four main themes that came out of the analysis of the interview, two were observed in Phase 1 results, they were the problems with maintenance planning on PM and RM. Apart from the data quality problems observed previously, additional important issues were observed: non-reporting of work orders (incomplete data), problem with manual reporting (lack of automated data collection), and improper data reporting. These results explain the poor quality of maintenance data from CMMS. Particularly, when the disparity of the data was presented, the participants gave a surprised reaction. In the evaluation of the data-driven tool, the quality of MES data were questioned. Some machine stops in MES data were uncategorized in that they were not maintenance related. Therefore, this calls for improving the data quality when it is put to use. On an ending note, the proposed data-driven tool was largely treated with positive response. Particularly, the relation between maintenance and productivity was highlighted.
Understanding, managing and communicating geomechanical mining risk
Published in Mining Technology, 2020
A further consideration beyond quantifying the level of uncertainty is how geomechanical data are managed. Geomechanical data should be shareable, transportable and secure and continuously kept up to date (Hadjigeorgiou 2012). For example, Hamman and Venter (2019) reports that the implemented data process flow at AngloGold Ashanti’s international operations includes well-defined procedures that include: collection of data,securing of data,reporting of data,validation,data packaging.
Enhanced data and methods for improving open and free global population grids: putting ‘leaving no one behind’ into practice
Published in International Journal of Digital Earth, 2020
Sergio Freire, Marcello Schiavina, Aneta J. Florczyk, Kytt MacManus, Martino Pesaresi, Christina Corbane, Olena Borkovska, Jane Mills, Linda Pistolesi, John Squires, Richard Sliuzas
New automated procedures to detect and mitigate major discrepancies and anomalies occurring in geospatial census data were developed, tested and implemented, while minimizing changes to the original data. Global and consistent remote sensing-derived data reporting on built-up presence was used to revise census units deemed as ‘unpopulated’ and to harmonize population distribution along coastlines. The two procedures employed for the detection of deficiencies in global geospatial census data obtained high rates of true positives, after validation and confirmation. The results also show that the targeted anomalies were significantly mitigated and that the baseline census database has improved, potentially benefitting other uses of the same statistical base. These outcomes are encouraging for further uses of free and open geoinformation derived from remote sensing. However, it must be recognized that assessing and monitoring progress of the new Development Agendas involves measuring many other population characteristics beyond population counts, for which proper census and surveys will remain invaluable sources, and that even accurate total population counts will ultimately continue to rely on high-quality enumerations and estimates.