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SAP CAR Online Training

SAP CAR online training

Introduction to SAP CAR online training:

SAP CAR online training where CAR is a customer activity repository is used to create retail applications. SAP customer activity repository is a authoritative new retail platform powered by SAP HANA based on the channel data foundation for pricing preparation near real inventory visibility with predictive and dynamic order sourcing capabilities. It enables retailer to collect and analyze information to particular customer in real time from different systems across numerous channels enabling 360 degrees inside the customer sales. To help faster the growth of partner eco system SAP CAR online training is now offered as virtual appliance deployed by SAP cloud appliance library and hosted on third party service provided of your choice.

Global online training will provide best SAP CAR training by our experts and also provide documents for SAP CAR online training which are prepared by our top professionals.

Mode of Training: We provide the Online mode of training and also corporate, virtual web training.

Duration Of Program: 30 Hours (Can Be Customized As Per Requirement).

Materials: Yes, we are providing materials for SAP CAR Online Training.

Course Fee: Please Register in Website, So that one of our Agent will assist You.

Trainer Experience: 15+ years.

 

SAP CAR Unified demand forecast:

Unified demand forecast leverages something called the demand data foundation which includes a reusable data layer that ropes planning analysis and forecasting business processes. In this we look about modeling it is an understanding of history using this historical demand data as input UDF tries to explain the historical sales and the impact that each demand influencing factor or DIF had on consumer demand in the past.

Modeling uses all of this historical transnational information offers product sales channels locations and it takes this time series based data stored in DDF and creates a model of what the man may look like in the future and there are more pre-processing before we even create the model we need to do some pre-processing and that’s the step that removes all of those unwanted extreme data points that may not be relevant and may throw off the model.

Some of the retail particular influences that modeling takes in to concern. In the earlier the Unified demand forecast quantifies the crash that every demand influencing factor had on customer demand in the past simply puts UDL calculates and quantifies the impact of those past factors that authority demand like promotions, Calendar, events and seasonality.

UDF calculates sales trends over time and then assumes the trends will continue as seen in that data the more history the more the trend is enhanced. We also provide SAP CAR UDF by industry experts. Along with SAP CAR online training SAP CAR UDF will also be provided in detailed manner by our well experienced trainers.

Day of week variations:

How do sales patterns vary from the beginning middle and end of the week do people spend more on paydays the first and fifteenth of the month?

Tracking the man by day of week is important since planned promotions or price change execution dates may vary based on the calendar.

Time Weighting:

Time weighting which basically means that UDF can wait recent sales more heavily than older sales to better align with the latest consumer demand the rational is that consumer preferences may change over time the idea is that older data tends to be less relevant to current demand and vice versa

Hierarchical Priors:

It allows you to enhance the modeling of some products that simply just don’t have enough chronological data or promotional data in the past examples are new lifecycle product or fashion products and in hierarchy there is the product hierarchy where a product and a specific location inherits values from other products in the same location. Location hierarchy means that a product in a specific location inherits values from the same product but in their locations so again priors are useful when we want to model for products that simply don’t have enough history.

The Philosophy of UDF is that it work out of the box the algorithm adjusts to quantify or not quantify the impact of each dip without the user needing to tune it for example you need to forecast for a fashion item then the model will automatically quantify a short life cycle for seasonality that does not repeat and/ or calculate the repeating seasonality and if there are no past trends then no trend will be quantified if there is no prior promotions then no promotion is quantified

Modeling:

 Model actually provides decomposition as UDF make an effort to explain the collision that every DIF had on customer demand in the past. Here decomposition is just that as output UDF produces a base demand value plus the added decomposition of demand by demand influencing factor so in this case we can see how the possessions of seasonality holidays prices plus offers are added to the baseline demand. We can also see the type of decomposition break down for the ultimate forecast. So again the model produces that past demand that output but I see it decomposed.

The forecast finally it is basically the model plus any planned inputs such as offers using the results from demand modeling and given inputs such as planned promotions and prices UDF can predict the effects of similar difficulties in the prospect and then use this to figure out what prospect demand should look like and again the collision of each factor that adds up to the total forecast can be detailed out in decomposition.

Forecast inputs:

Forecast inputs before we set that the model plus any plan inputs equals the forecast. A simple example of a plan input would be If I would ask what if I created a promotion for the channels and products categories for this time period and these locations what would my sales lift be.

Forecast outputs:

In this we start with Forecast confidence index or FCI it is a measure of the amount of data available to provide a true look at demand. It is a number the FCI is a statistical indicator of confidence in a particular unit forecast it is always calculated for a specific product at a specific location the more relevant historical data you have the higher the FCI should be the system can also estimate which of the dips considered for a particular forecast most likely led to Low FCI. For example we may have a low FCI because we have a new offer type in the future that has not yet been observed in the past.

Forecasted unit sales is the output that we are looking for and UDF provides the decomposed forecast number to assist us realize the impact of each dip on the forecast since it is always hard to trust the number that outcomes of a system especially when you’re the retail analyst there are forecast analytics and one good example is the analyzed forecast app that helps us visualize how did the model gets generated what dips impacted the model and the eventual forecast such as seasons promotions and so on.

 

Why should we put the SAP CAR online training in the cloud and why Cloud?

Cloud is a simplified landscape agile platform for continuous innovation and fast time to value. It lower totals cost of owner ship and quicker execution can also be done. CAR rapid deployment solutions can do quick execution and preconfigured on premises and cloud solutions. It gives fixed price implementation services. Global online training’s offer both online training’s and also corporate training’s for the individuals at flexible hours to know more information about this SAP CAR online training please register with our website.

 

Conclusion for SAP CAR online training:

The average pay scale for SAP can also be defined based on the gender for female is 17% their salary starts from Rs 515,210 – Rs 1,895,250 and for male is 83% and their salary starts from Rs 326,811 – Rs 2,269,098. The use of SAP CAR online training is SAP Customer Activity Repository is a basis that gathers transactional data that was earlier spread over numerous independent applications in various formats. The repository gives a regular basis and a coordinated multi channel transaction data model for all intense applications. SAP CAR online training is able to be utilizing to maintain the existing Loss Prevention Analytics (LPA) business process of the Store Analytics company situation. SAP CAR online training is a way based on an inventive SAP HANA database. This platform changes the technique of data processing.

Global online trainings will provide SAP CAR online training with well experienced corporate trainers and we also provide the trainings during the weekends and weekdays based on the students demand and also provide project with the reasonable price.

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