Scudata

esProc SPL’s Grouping Operations: The Most Powerful in History, Bar None 🤗 🤗 🤗 #Grouping Operations #esProcSPL #sql #python

The Simplest Eight Queens Code You’ll Find Online 🤩

Why Developers Are Ditching SQL Pain Points with Open-Source SPL？ 😄 #SQL #esProcSPL #PainPoint #developer #Data analysis

SQL does data analysis dilemma, query language can not answer the truth 😜 #sql #dataanalysis #language #esProcSPL

The Breaker of Closed Database Computing System---Open-source SPL Databases are mostly used for computing data in real-world situations, particularly in big data scenarios, and almost completely for OLAP scenarios. Database storage aims primarily to serve computations, too. Databases have rather good computing abilities, far better than most other software products, so they are often deployed to meet computing needs. 🙃 Yet a closed system is not only unnecessary but harmful to a product intended for computations. That’s why today databases become more and more awkward in handling data processing tasks. 🤩 #database #OLAP #esProcSPL #SPL

Are There “Queries over Trillion-Row Tables in Seconds”? 🙃 Is “N-Times Faster Than ORACLE” an Exaggeration? 🤨 #oracle #esProc #Trillion-Row Tables

Two major shortcomings of Python in enterprise applications! 😜 Relational database is the most common data storage scheme, and hence SQL naturally becomes the first choice for data processing. However, as the complexity of enterprise applications advances, data operation and processing implemented in SQL begins to encounter many serious problems at framework level. Specifically, it is difficult to migrate complex SQL (stored procedures); it imposes a heavy burden on the database since all processing and computing of data are executed in database, which has become a bottleneck of the whole application; Sharing a database by multiple applications will easily lead to strong coupling between applications. Therefore, more and more modern applications begin to resort to other technologies to process data. 🤨 Among these technologies, Python is a good choice for the reason that: i)it offers powerful library, and supports various data sources; ii) its syntax is flexible and can express complex calculation process; iii)it can be stored independently or coupled with front-end applications, and is easy to maintain; iv) it provides a complete IDE, which allows us to debug conveniently. Therefore, more and more applications begin to use Python to process data. 🤗 However, two major shortcomings exist when Python is used for enterprise applications. 🤪 #python #data #IDE #process data #enterprise applications #esProcSPL

Although AI modeling & predicting in Python is popular, SPL is also a good alternative to get started 😜 There are many tools that can be used for AI modeling and prediction, such as Python, R, SAS and SPSS, where Python is very popular because it is simple, easy to learn, rich in data science libraries, open source and free. However, modeling in Python is still complicated for programmers who are not very familiar with data modeling algorithms. In many cases, they have no idea to start and do not know which algorithm to choose when they have data. In fact, SPL is also a good choice when performing data analysis and modeling task since SPL is simpler and easier to use than Python and fast in calculation speed. In addition, SPL provides an interactive interface that is very friendly to data analysis, and also provides easy-to-use automated data modeling functionality and some data processing and statistical functions. 🤗 #Python #R #SAS #SPSS #opensource #AI #esProcSPL

10 lines of code to achieve handwritten digit recognition 😜 Recognizing handwritten Arabic numbers is very simple for human beings, but it is still somewhat complicated for programs. 🤗 However, with the popularization of machine learning technology, it is not difficult to implement a program that can recognize handwritten numbers using over 10 lines of code. This is because there are too many machine learning models that can be directly used, such as TensorFlow and Caffe. There are ready-made installation packages available in Python, and for writing a program that recognizes numbers, a little over 10 lines of code is enough. 🙄 However, what I want to do is to completely implement such a program from scratch without using any third-party libraries. The reason for doing this is because you can deeply understand the principles of machine learning by implementing it yourself. 😄 #program #esProcSPL #SPL #code #

DCM: A New Member of Middleware Family 🙃 Contemporary applications feed on data. Data computations are everywhere – reporting statistics, data analysis and business transaction to name a few. At present, relational databases and other related technologies constitute the mainstream data processing capabilities. Hardcoding in high-level languages like Java can achieve all computations, but it is not nearly as convenient as SQL-based-databases. The latter is still the backbone of today’s data processing systems. On the other hand, progress in information technology is giving rise to new concepts and frameworks such as the separation between storage and computation, microservices, moving computations frontward and edge computing. The heavy and closed databases seem to become increasingly inconvenient in handling the new scenarios. Databases require loading data to them for further computations. The problem is that data loading presents inefficiencies, large resource consumption, and non-real-time-ness when diverse data sources are involved. Sometimes, data just needs to be used temporarily and storing it permanently in the database outweighs the advantages. Databases are also hard to embed for scenarios like microservices and edge computing that need to deploy the computing capability frontward at the application. All those problems can be solved if there is a data computing & processing technology that is database-independent, has open computational capability and can be embedded and integrated in applications. Such a technology is called Data Computing Middleware (abbreviated as DCM).  #DCM #Middleware #esProcSPL #SPL