CCP Preparation Course

Become an MQL4 Programmer!If you are a trader looking for ways to make trading simpler and more efficient, you've come to the right place. Leverage technology to your advantage!If you are a trader-programmer who would like to bring your programming and algorithmic trading skills to the next level, this course is for you. No need to reinvent the wheel!If you are somebody just looking for a new hobby, try algorithmic trading through this course. There are only so many hobbies where you are compensated for doing something great!This course is the most intensive, yet straightforward, course for the MQL4 programming language - based on years of experience of an MQL4 programmer. Probably the fastest way to learn how to build complex trading robots and scripts using the MQL4 programming language, for traders!The course is fast-paced, but designed with the trader in mind:Low information diet - take only what you need to move on to the next lessonLearn the rules of trading, which you may use as well to enhance your own manual tradingDevelop MQL4 programming skills, and learn to apply to solve common problems in both manual and automated tradingBy the end of this course, students would be able to independently develop robust and efficient trading robots and scripts based on their own ideas, and expand on their programming knowledge on their own, as an MQL4 programmer!This is programming course is aimed at making the life of the trader easier by enabling one to develop his or her own MQL4 programs, and augment his or her trading skills through automation.

Traders on Metatrader 4 or 5 have the ability to follow their trades via mobile applications Mt4 and Mt5 respectively. The mobile versions of these apps comes with the ability to visualize charts, and apply default indicators. However, one can not control, upload a custom indicator nor an Expert Advisor. However, even though the mobile app provides us with some functionality we can not fully rely on it. Secondly there is a possibility that one can see them selves in front of a computer and they don't have their mobile device anywhere near, and the computer in front of them has no Metatrader installed, but the user wants to be able to control his or her trades. The CourseThis course aims to equip learners with the skills on how to create a link between Metatrader 5 and Telegram. Open, close, and manipulate trades from telegram. The user will get notifications on their telegram group, channel or even Telegram bot for every action that Metatrader executes. Receive Screenshots of your favorite custom indicator, on any chart you wish, and many more. The course is structured from simple to understand to more complex functionality, were the user will learn principles that they can utilize and combine with any other similar platform.

SAP CO Material Ledger with First in-first out (FIFO):How Material Ledger can approach with First in, first out (FIFO) in S/4 HANA 2020 (MM, Production, SD cycle flows)Balance Sheet ValuationIf the Companies report their Inventory values in different ways."Balance sheet" preparation for Legal ,Company policy rules for Internal management objectives also for Tax purpose.The different ways to value inventory is based on how the policy for inventory valuation treats the inflationary factors in the market.The most and main approach of nowadays companies following Inventory withdrawal and valuation in SAP is either "First in-first out (FIFO)" and Average Cost MethodsFirst in, first out (FIFO):"FIFO" stands for first-in, first-out, meaning that the oldest inventory items are recorded as consumed if it is RM(procured material), and Sold if it is FG(production material) first. In other words, the cost associated with the inventory that was purchased/Produced first is the cost expensed first.An approach to inventory management with FIFO method either withdrawal and or valuation procedure in which materials and products are actually withdrawn from stock for sale and or use in the production/process order of their manufacturing (i.e. the first goods received are - or are deemed to be - the first to be issued).Testing with MM, Production and SD Cycles "Material Ledger with First In, First Out (FIFO)"1) Raw material (procured from outside) with price control “V” and determination “2”. FIFO Inventory valuation procedure without Actual Costing/Material Ledger execution-CKMLCP in the same period.2) Raw material (procured from outside) with price control “S” and determination “3”. FIFO withdrawal method and valuation procedure with Actual Costing/Material Ledger execution-CKMLCP in different periods.

Course DescriptionIn today’s data-driven world, organizations are dealing with massive amounts of data generated every second. Big Data technologies have become essential for efficiently processing, storing, and analyzing this data to drive business insights. Whether you are a beginner, fresher, or an experienced professional looking to transition into Big Data Engineering, this course is designed to take you from zero to expert level with real-world, end-to-end projects.This comprehensive Big Data Bootcamp will help you master the most in-demand technologies like Hadoop, Apache Spark, Kafka, Flink, and cloud platforms like AWS, Azure, and GCP. You will learn how to build scalable data pipelines, perform batch and real-time data processing, and work with distributed computing frameworks.We will start from the basics, explaining the fundamental concepts of Big Data and its ecosystem, and gradually move toward advanced topics, ensuring you gain practical experience through hands-on projects.What You Will Learn?Big Data Foundations – Understand the 3Vs (Volume, Velocity, Variety) and how Big Data technologies solve real-world problems.Data Engineering Pipelines – Learn how to design ETL workflows, ingest data from multiple sources, transform it, and store it efficiently.Big Data Processing – Gain expertise in batch processing with Apache Spark and real-time streaming with Kafka and Flink.Cloud-Based Big Data Solutions – Deploy and manage Big Data solutions on Azure, and GCP using servicesEnd-to-End Projects – Work on industry-relevant projects, implementing scalable architectures, data pipelines, and analytics.Performance Optimization – Understand best practices for optimizing Big Data workflows for efficiency and scalability.Who is This Course For?Beginners Freshers – No prior experience need

Group reporting consists of topics such as consolidation process and analytical reports and supports the computation, creation, and disclosure of consolidated reports that provide information on the performance of a corporate group.SAP Group Reporting Data CollectionSAP Group Reporting Data Collection helps you gather financial data for your business units. The app is hosted on the SAP Business Technology Platform and relies on data such as master data and allowed breakdowns from group reporting within SAP S/4HANA.With SAP Group Reporting Data Collection, you can map data, create forms, design your own reports, and use these or the predefined reports to collect data as part of your data preparation for consolidation.SAP Analytics Cloud(SAC) provides deep insights into your business using reporting and data visualization, which will help you make better decisions.With live data connections, the integration between SAP S/4HANA Finance for group reporting and SAC enables business analysis at group or corporate level without data replication.In this release, the following detail and overview reports are available out of the box:Consolidated report book for actual dataPeriodic overview report bookActual and budget comparison report bookActual, budget, and forecast comparison report bookPredictive consolidated P L analysisGroup financial KPIs overviewConsolidationA complete consolidation process typically starts with preparatory steps, such as setting global parameters, checking the master data of your organizational units and financial statement (FS) items, and specifying effective exchange rates.After that, you can proceed with collecting data reported by consolidation units, and standardizing the data with features available in the Data Monitor. When the

News are the daily fuel for fear and greed in our daily lives. News determine how we plan for our future and anticipate our fortunes or peril. The informed are always safe, that’s the law of the jungle.The forex market is a beast fueled by nothing other than fear and greed. It represents the true nature of human behavior. It’s a competitive jungle where the fittest are poised to survive. It’s a chamber of fortunes and pain, married to one another like yin and Yang.Because news promotes behaviors of fear and greed, it is news that drives chaos and volatility in the forex market. It is news that causes irrational behavior of the markets and it is news that causes the markets to trend. Without news, there would be no volatility which attracts investors to the forex market, there would be no greed that causes buying and no fear that causes selling. Markets would stagger and stagnate for long periods, losing their appeal as opportunity makers.News that affects the forex market is collected within the Economic calendar. For algorithmic traders, reliable and timely news is paramount and this is where the MQL5 economic calendar shines. This is mainly because even though economic data websites are everywhere, integrating them correctly into your Expert Advisors (EAs) can be very challenging.MQL5's calendar resides within the MetaTrader platform itself. This eliminates the need for external data feeds, ensuring seamless integration and minimal latency. Your EA receives economic event updates directly, allowing for near-instantaneous responses to market shifts triggered by data releases.Also the MQL5’s economic calendar offers a dedicated set of functions specifically designed for EAs. These functions allow you to efficiently query the calendar for upcoming events, filter by specific data types (interest rates, employment figures, etc.),and extract crucial details like release time and forecast values. This streamlined approach saves you the hassle of parsing exter