## Time series Series with Power BI- Arima Model-Part 11

Posted on Oct 2, 2017

In the last post, I have explained the d value for model ARIMA (p,d,q). In this post, I am going to show how to identify the p and q values as below. one of the main difference between exponential smoothing and Arima is that Arima considers the correlation of a value at a time with ...

## Time series Series with Power BI- Arima Model-Part 10

Posted on Sep 25, 2017

In this post, I want to explain the ARIM model (Autoregressive Integrated Moving Average). Exponential smoothing could not consider the relationship between the values in the different time span. while ARIMA able to handle these data. ARIMA Model needs three variables. ARIMA(p,d,q) First, let start with explanation of d value what is d? The first ...

## Draw Slope Chart in Power BI: Part 8

Posted on Sep 5, 2017

Slope chart can be used for comparing data between two different time periods. it is a very easy way to depict the difference between to time, two elements or any other two attributes. The slope charts can be used to study the correlation between variables or to study the change in the same variable between ...

## New Series of Time Series: Power BI Custom Visual (Part 5)

Posted on Aug 18, 2017

In previous posts, I have explained some basic concepts of time series. In the first post I have explained the basic concepts of time series, and in second and third posts I have explained: “Exponential Smoothing” for forecasting data without trend, and with the trend. In the last post, I have explained how we can ...

## New Series of Time Series: Part 3 (Holt’s Exponential Smoothing)

Posted on Aug 7, 2017

In the last posts, I have explained the main concepts behind the Timeseries (Post 1) and  in the second one a simple forecasting approach name as “Exponential Smoothing” has been proposed Post 2. In this post I am going to show how to do see the error of forecasting and also how to forecast when ...

## New Series of Time Series: Part 2 (Exponential Smoothing)

Posted on Aug 3, 2017

In the last post , I have explained the main concepts behind the timeseries. In this post, I am going to show how we can forecast for some periods. In the last post, I have mentioned that there is a possibility to have “seasonality” “Trend” and  errors (residual) in one dataset: Seasonality+Trend+Residual we call it as ...

## Interactive Charts using R and Power BI: Create Custom Visual Part 3

Posted on Jul 10, 2017

In the last two posts (Part 1 and 2), I have explained the main process of creating the R custom Visual Packages in Power BI. there are some parts that still need improvement which I will do in next posts. In this post, I am going to show different R charts that can be used ...

## Neural Network Concepts Part 1

Posted on Jun 26, 2017

In this and next one, I will share my understanding on Neural Network and how to write the related R code inside the Power BI. First, in this post I am going to explain what is main concept behind the Neural Network and How it works .The video https://www.youtube.com/watch?v=DG5-UyRBQD4&spfreload=10 helped me  a lot to get better ...

## Speaking Files in Microsoft Data Insight Summit 2017

Posted on Jun 23, 2017

Microsoft Data insight Summit 2017 has been held in Seattle from 12 to 13 Jun. It is the main conference for Microsoft Data Analysis with Power BI. All interesting and new topics in Power BI has been presented. Most of the speakers are from Microsoft product team or  experienced speakers in this fields. there are ...