# predicting multivariate time series with little data

I have 1 week of data formatted in the following way in R.

$$\begin{array}{c} \text{Category1} & \text{Category2} & \text{Category3} & \text{Date} & \text{Metric1} & \text{Metric2} & \text{...} & \text{Metric7} \\ \hline X & a & 1 & 7/1/17 \\ X & a & 2 & 7/2/17 \\ X & b & 1 & 7/3/17 \end{array}$$

My goal is to predict Metric1 on a future date, ex. 7/15/17.

1st question - can you roughly describe how you might approach this? I have little time-series experience. I'm reading some materials but advice is welcome.

2nd question - broadly speaking, is this even worthwhile when I have only 1 week of data? Am I stuck until I collect more?

Hoping for a bit more explanation or detail, as a time-series beginner. Also that thread doesn't seem to have an accepted answer.