You need to create a new data warehouse – either none exists, or you have to replace your data warehouse because it is not convenient anymore. Software support and automation in the construction of DL, DWH & DM is currently limited to data integration tools (ETL).
To create a new DWH with the conventional ETL tools is time-consuming, expensive and usually requires external consultants.
AnalyticsCreator helps you to automate the design, creation, maintenance, and deployment process of DL, DWH, DM. Automation brings a high standardization in all steps and the modern design standards fulfil their goal. Sometimes it is faster to create a new data warehouse by using DWA and a modern approach, without changing the presentation layer.
Your data warehouse needs an all-encompassing architectural update – perhaps your DWH is not applicable to new business needs – new heterogeneous data sources, architectural dead ends…
However, modern modelling approaches like data vault and hybrid techniques, and a need for historised data, should comply with today’s best practices.
The challenges are to identify the good from the bad parts of your data warehouse. Obsolete documentation, differing design understandings from several consultants of the actual model, and the time and cost to rebuild the data warehouse are very big challenges.
With automation, you standardise all parts of the design and build processes of DWH and DM, by using modern modelling approaches. The new lifecycle process run much faster. Changes in business requirements, changes in source data and extensions can be adapted at a single point – automation takes care of consistency in all layers.
You have new influences and you want to see the business impact in adopting new data models and analysis.
There is a short timeslot, a small budget, and no free resources in manpower and hardware infrastructure.
On-demand, in the cloud or on-premises, you can set up a prototyping environment in a few hours and connect to your source data or several DWH-layers. The AC assistant will analyse & advise you how to deploy the analytic application in a short time and with a low budget.
The management sometimes changes the business model, the market strategy, or want to have new analysis or reports. Predictive analytics requires historical data or new data sources like unstructured data from the cloud (hadoop, nosql).
The internal IT have an overload of tasks and don’t always have time to react quickly. Sometimes the resources for BI and Analytics are limited.
The biggest benefit would be the time & cost factor. The “time to market” of an analytic application/report decreases rapidly. The project owner gets results from a prototype in much fewer days. The agility to create new business apps becomes a new dimension.
With automation tools the organisation chooses the way to greater independence from the BI paradigm, set by BI vendors. It also changes the way consultants work. Internal and external consultants work with the design UI which generates the code and standardises any handwritten code. The failure rate of projects decreases instantly.
You have a lot of changing data.
You still don’t know how you will analyze the changing data but you understand that you should start to store all the data and data changes you can reach as soon as possible because without the data change history you cannot analyze.
Using AC you can very quickly create the staging data warehouse which will contain historical data. Later you can decide how you will analyze your data and extend your data warehouse.