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Say I have data which looks like data1 - this is "matrix" like data (is there a better descriptor?). The data looks like a matrix, and at each point in the matrix, it has a value. I can plot these in ListContourPlot and the like. e.g.

datafunction = MultinormalDistribution[0, 0, 2, 1/2, 1/2, 1];

(* matrix like data *) 

data1 = N[ Table[PDF[datafunction, x, y] /. x -> xinsert, y -> yinsert, xinsert, -4, 4, 1, yinsert, -2, 2, 1]];
ListContourPlot[data1]

However, I can also create the same effect by making "coordinate" like data, where the data is a list of coordinates.

(* coordinate like data *) 

data2 = RandomVariate[MultinormalDistribution[0, 0, 2, 1/2, 1/2, 1], 1000];
ListPlot[data2]

How would I convert data1 into data2? How do I convert matrix-like into coordinate-like?

I need to do some PCA analysis, I require the data to be in the form of individual points.

The reshaping can be done in several ways. Below is given one using SparseArray.

First generating the data (simpler than in the question):

datafunction = MultinormalDistribution[0, 0, 2, 1/2, 1/2, 1];

data1 = N[Table[PDF[datafunction][x, y], x, -4, 4, 1, y, -2, 2, 1]];

MatrixForm[data1]

Make index-to-value associations corresponding to the ranges used to make data1:

aX = AssociationThread[Range[Length[#]], #] &@Range[-4, 4, 1];
aY = AssociationThread[Range[Length[#]], #] &@Range[-2, 2, 1];

Convert to a sparse array, take the corresponding rules, and map the x,y indexes to the actual x's and y's.

arules = Most[ArrayRules[SparseArray[data1]]];
data2 = Map[aX[#[[1, 1]]], aY[#[[1, 2]]], #[[2]] &, arules]

Plot (note the axes ticks):

ListContourPlot[data2]

An alternative approach based on Rescaleing the "NonzeroPositions" of SparseArray[data1]:

xrange = -4, 4;
yrange = -2, 2;
sa = SparseArray[data1];
nzp = sa["NonzeroPositions"];
nzv = sa["NonzeroValues"];
data2b = Join[Transpose[Rescale[#, MinMax@#, #2] & @@@
 Thread[ Transpose@nzp, xrange, yrange]], List /@ nzv, 2];

data2b == data2 (* from Anton's answer *)

True