Category: uncategorized
SPL general table operations
Filter out the records that meet the conditions from the data table.
Looking for the Best Excel Add-ins
Data analysts often turn to add-ins when they encounter complicated computations in Excel. Here we examine and compare some common add-ins in terms of deployment process, development efficiency, application fluidity and, particularly, computational capabilities. esProc SPL shows more excellent performance than others. Looking Looking for the Best Excel Add-ins for details.
Looking for the Best Lightweight Data Analysis Script Tools
A lightweight desktop script tool is a must-have for data analysts. But how do you know which is the most suitable one? Let me walk you through four top script tools to experience and compare their usability, dev efficiency, types of supported data sources, functions for performing structured computations, and, particularly, algorithm implementation performances to find the best one. And esProc SPL is the winner. Looking for the Best Lightweight Data Analysis Script Tools for details。
What programming language should business people learn?
Through programming, the business people can overcome the difficulties of manual operation of Excel, and greatly improve work efficiency. This paper carefully selected four programming languages, from the installation, debugging, tabular data calculation and other aspects of in-depth comparison, and focused on the learning difficulty, esProc SPL performs well in these tools, and is most suitable for business people to learn.
Which Is the Best Technique for Separating Cold Data from Hot Data?
As business expands, the database or the data warehouse for an OLAP application stores more and more data, and their workload increases. This results in slower response times. Scaling up or scaling out the database is not enough to solve the problem because both are not only expensive but can hardly push the performance up once the database capacity reaches the limit.
Separating cold data from hot data is a better solution. It stores and computes the small amount of frequently accessed hot data and the large amount of seldom accessed cold data separately in order to reduce database workload and increase the response times for queries.
