From: Secure big data ecosystem architecture: challenges and solutions
DAMA knowledge area | Solution | Study | Frequency | Percentage |
---|---|---|---|---|
Data architecture | Architecture security | s11, s13, s18, s22, s28, s30, s35, s40, s54 | 9 | 12 |
Data modeling and design | Communication security | s11, s21, s22, s23, s30, s35, s40, s41 | 8 | 10 |
 | Threat modeling/risk assessment | s10, s18, s19, s21, s24, s29, s30, s36, s39, s48, s54, s70, s78 | 13 | 17 |
 | Intrusion recognition | s13, s18, s39 | 3 | 4 |
Data storage and operations | Incorporate end point validation and response capabilities | s28, s33, s36, s54 | 4 | 5 |
 | Secure queries | s12, s16, s28 | 3 | 4 |
 | Secure data collection, storage, usage, transaction logs and destruction | s8, s12, s18, s23, s57s28, s33, s35, s36, s37, s39, s54, s57, s69, s71, s72, s73 | 16 | 20 |
 | Distributed sources for data | s10, s23, s28, s36, s38 | 5 | 7 |
 | Data transformation | s13, s23, s28, s36 | 5 | 7% |
 | Machine learning algorithms | s39, s46, s55 | 3 | 4 |
 | Data classification | s69, s72, s73 | 3 | 4 |
Data security | Encryption | s4, s10, s11, s12, s16, s21, s22, s26, s28, s30, s31, s35, s36, s38, s40, s41, s42, s45, s47, s53, s54, s57, s59, s65, s66, s77, s78 | 27 | 34 |
 | User validation | s11, S19, s26, s28, s30, s37, s54, s77 | 8 | 10 |
 | Confidentiality | s16, s26, s38, s39, s48, s57, s66, s69 | 8 | 10 |
 | Skills | s13, s15, s18, s27, s37 | 5 | 7 |
 | Differential privacy | s7, s10, s11, s40, s57, s69, s71, s73, s75 | 9 | 11 |
 | Latent data privacy | s64 | 1 | 2 |
 | Data-driven privacy preserving | s67, s68, s71, s76 | 4 | 5 |
Data integration and interoperability | Â | Â | 0 | 0 |
Documents and contents | Granular access control | s10, s11, s15, s16, s21, s24, s26, s28, s29, s30, s31, s33, s36, s45, s48, s54, s55, s66, s69, s76 | 20 | 25 |
 | Data anonymization | s7, s10, s12, s14, s16, s19, s21, s29, s31, s35, s42, s44, s45, s47, s48, s51, s57, s58, s59, s68, s69, s71, s73, s77 | 24 | 31 |
 | Granular audits | s21, s28, s33, s54, s72, s76, s78 | 7 | 9 |
 | User education | s28, s44 | 2 | 3 |
Reference and master data | Recovery | s15, s21 | 2 | 3 |
Data warehousing and business intelligence | Â | Â | 0 | 0 |
Meta-data | Storage of encrypted header information | S35 | 1 | 2 |
 | Provenance metadata | s4, s23, s42, s67, s72 | 5 | 6 |
Data quality | Integrity | s4, s10, s14, s16, s22, s23, s26, s28, s30, s35, s38, s39, s42, s44, s48, s51, s53, s55, s57, s69 | 20 | 25 |
Data governance | Privacy at social network | s13, s19, s23, s28, s38, s49, s52, s53, s78 | 9 | 11 |
 | Policies, laws or government | s1, s8, s10, s13, s15, s19, s21, s59, s62s22, s23, s25, s28, s29, s31, s35, s37, s38, s40, s41, s44, s49, s51, s56, s57, s69, s72, s73, s76 | 27 | 34 |