Evolution of storage costs
Stored Data Volumes, Storage Cost and Need for Knowledge
In the last two decades, data storage systems have known a powerful evolution that has lead to a exponential increase
of the amount of data stored on digital supports and implicitly to a
decrease of the storage costs. The amount of stored data has increased in such a way that it has outrun the ability of processing systems to provide easy access to
knowledge contained in data.
Nowadays, companies have accumulated large amounts of data that need to be organized, shared, managed and used by Business Intelligence in order to improve management process.
The main challenges of companies confronted with this fast increase of their
stored data are to exploit them at the lowest cost and to determine an
efficient way to value data by knowledge discovery. Therefore, they have to
answer several questions:
- What strategies for establishing a knowledge discovery process?
- What are the possible ways to value the increasing amount of data?
- What are the right data to analyze?
- What kind of analyses are addapted for discovering knowledge in my data?
We can assist you in acquiring the expected knowledge
Rithme can work with you to develop and successfully implement a complete data analysis strategy that meets your specific
needs in terms of knowledge discovery.
We can guide you through the implementation of the whole process, from data collecting and organizing to the extraction of knowledge and
its deployment in your business intelligence process (see solutions). Along this process Rithme can
provide you with highly trained specialists, a full range of database management services
including advise on cleaning and enhancing your existing data, database hosting,
data integration and user friendly tools to analyze
and manipulate your data.
We already developed and implemented data analysis strategies throughout
collaboration with Research Divisions of major world actors in cosmetic
pharmaceutical industries (Novartis, Lundbeck) requiring high adaptability and confidentiality.
Companies confronted with the issue of managing their increasing data realized that the costs of storing, updating and especially efficient using of data to improve company’s performance and profitability take the company away from the borders of its core know-how.
Most enterprises store data in their own storage systems. However, the skills and expertise to manage and develop data analysis are unlikely to exist in their business, in which case the effective solution is to externalize the knowledge discovery process. Therefore, two alternative strategies arise:
- The first strategy is to orient the data analysis process to specialized software editors (i.e. SAS, SPSS, etc.), in which case data analysis skills are strongly recommended for the use of the chosen data mining software. Nevertheless, “prescribing” the acquisition and use of a software would correspond to the prescription of a solution without having thoroughly identified the real
business specificities and analysis needs, just like one would ask a drug company to cure
patients by prescribing medicines without having examined their symptoms.
- The second strategy consists in outsourcing the data analysis process to a specialized professionals, like RITHME, with an expertise in
identifying needs in data management, data maintenance, appropriate
feature selection and finally knowledge extraction - the last step in a data analysis process.