Sources and Data Processing
In order to get to a holistic vision of the market and its phenomena it’s important to process all the company raw data coming from every data source. Data are heterogeneous by source and definition, aggregated and disaggregated at different granularities, available in massive quantities but questionable with regard of the quality. So, collecting, transforming, and even cleansing them to determine their relationship is the first step to build a strong strategy. Such a process, called ETL (Extraction – Trasformation – Loading), is the basis for every Business Intelligence project.
In a fluid reality the concept of Data Warehouse is limiting
In 2010 James Dixon conied the term “Data Lake” to address the raw data available for a company and coming from diverse sources, which have to be managed in their entirety.
Data Quality is the key point
On Premise Data, Data Warehouse, Open Data, Data Could, IoT Data, and Big Data. All the company data come from diverse sources, so are likely to come in different formats. From Data Lakes to Data Warehouses, ITReview guarantees the maximum quality in collecting and processing raw data. At this step you create the right conditions for a Data Analytics and/or Business Intelligence project.
Converting heterogeneous data is like tuning the instruments of the same orchestra
Regarding Big Data and Data Lakes, ITReview relies on Trifacta, the Data Wrangling platform able to manage raw data coming from multiple sources and provide immediate information from them in a short period of time. Thanks to Machine Learning, Trifacta classifies also transformation and manipulation of the data needed by the user. Based on self-learning algorithms, TriFacta created a catalog of “Data as a service” ready to be used by Data Scientists, or by traditional Data and Business Intelligence Analysts.
Refining Raw data into value
Thanks to It Reviews’ tools, end users can formulate questions and explore complex information having immediate feedback and acquiring knowledge for the next step: Data Analytics.