I joined HP and Microsoft Professional Luncheon in order to find out the latest trends, best practices and innovations in business intelligence (BI), analytic applications and data warehousing through the HP and Microsoft products and solutions.
HP SQL Server Fast Track Data Warehouse was mentioned to reduce costs, risks and implementation time. Moreover, it only cost $6.6K per terabyte at 95TB.
HP Enterprise SQL Optimizer on the HP ProLiant DL980G7 was demonstrated. The sample optimization result was showed.
Mr. Hon concluded that people talking about BI meant "Reporting" but BI should be assisted leaders to make decision for business faster through "In-memory Computing".
The second speaker was Mr. Michael Chong (Solution Manager, Microsoft Hong Kong) and his topic entitled "Microsoft Business Analytic Platform & Data Warehouse Solution".
Mr. Chong said that it was challenging to answer Business questions with hard data in the absence of a Data Warehouse. It was because of huge varieties of data formats.
Then he demonstrated a complete Business Analytic Platform through Powerpivot through Excel 2013 (which had not launched yet).
Sales performance analysis was demonstrated and it seems very faster for any ad hoc analysis request.
Finally, Mr. Chong mentioned the Big Data Case Study for Thailand DSI to us. He said that we needed to face information overflow today and we needed to organize many unstructured data. "In-memory Analytics" considered the velocity and volume of data analysis.
Mr. Chong said that it was challenging to answer Business questions with hard data in the absence of a Data Warehouse. It was because of huge varieties of data formats.
Then he demonstrated a complete Business Analytic Platform through Powerpivot through Excel 2013 (which had not launched yet).
Sales performance analysis was demonstrated and it seems very faster for any ad hoc analysis request.
Finally, Mr. Chong mentioned the Big Data Case Study for Thailand DSI to us. He said that we needed to face information overflow today and we needed to organize many unstructured data. "In-memory Analytics" considered the velocity and volume of data analysis.
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