# Conceptual Framework for Implementing Temporal Big Data Analytics in Companies
## Appendix A
So, I would look at the temporal dimension more from the perspective of business cases than of such a concept as time analytics.\"_  
As seen from the utterances being cited, the focus participants consider bringing the time dimension to the forefront as an advantage of the proposed framework. Some of them only deal with simple, calendar time (time series)--which more formally may be described as linear point time, some of them are also aware of richer temporal analyses, such as causal relationships or sequences of events. Regardless of experience, everyone admitted that the inclusion of the time dimension as the primary dimension in big data analytics can bring great benefits, even if time will not be used in every business case. _Outcome 2: Consistency of the proposed framework_  
Question: _Does the presented framework consistently combine the following aspects: technological, analytical, strategic, and organizational?_  
The consistency of any solution is one of the most important conditions for its success in practice. In the area of implementing business IT solutions, it is, therefore, necessary to coherently combine organizational and technological issues. As the proposed framework is about business analytics, it must also consistently integrate strategy and analytics. _\"In my corporate experience, it all fits together. From the academic point of view, the entire described process is identically mapped to the processes that exist in the company.\"_  
_\"It describes the reality that is actually happening quite in a model way.\"_  
_\"I have been working at the university for 25 years, I have also worked in many corporations, I deal with systems of the financial area. The model you showed is consistent with the broadly understood model of implementing IT solutions: first you need to do an analysis, examine the needs, the current state, and only use various methods to develop the software, implement it, and then evaluate the solution and any possible adjustments.\"_\"The proposed framework combines the technological, analytical, strategic, and organizational levels as coherently as possible.\"  
\"At this level of generality, the framework is consistent, but I do not fully imagine what it will look like when going down, what the requirements and performance indicators will be. So, on the academic level of the framework description, everything is fine, but the devil is in the details--how it will work in practice. By contrast, as a framework, the solution is clear and consistent.\"  
All the participants who addressed this question pointed out its consistency with regard to company, technology, business strategy, and big data analytics. The compliance of the proposed solution with generally accepted IT implementation standards was also underlined. However, one of the debaters expressed doubts about the requirements and performance indicators of the proposed framework. As for the latter, this issue will be addressed in question 4. As for the former, the requirements for the BDA implementation framework are indicated in Section 4 but were not included in the presentation to the focus group participants. The requirements for a specific TBDA implementation in a company will of course depend on business conditions, but it can be assumed that the coherence of the proposed framework and its basis on the TBDMM maturity model will allow for the formulation of consistent requirements for specific TBDA implementations. The use of lean, agile, and leagile concepts in the framework as a way to capture the temporality of BDA  
Question: Is it justified to use agile, lean, and mixed (lagile) solutions in the proposed framework? Lean, agile, and leagile approaches are--apart from temporality--a distinguishing feature of the proposed framework. Hence the question of the legitimacy of their use. \"The use of agile methodologies is now a standard. Leagile approach: this is what I think the most about because my experience is such that it gets a little mixed up of course, especially lean, and agile.