BUG: pd.Series() constructor with 2d NumPy array raises bare Exception
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

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#### Code Sample, a copy-pastable example

```python
import pandas as pd
import numpy as np
arr = np.random.rand(10, 4)
pd.Series(arr)
```

I get this output

```
---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
<ipython-input-4-974eca309da1> in <module>
      2 import numpy as np
      3 arr = np.random.rand(10, 4)
----> 4 pd.Series(arr)

~/.pyenv/versions/3.8.3/envs/census/lib/python3.8/site-packages/pandas/core/series.py in __init__(self, data, index, dtype, name, copy, fastpath)
    325                     data = data.copy()
    326             else:
--> 327                 data = sanitize_array(data, index, dtype, copy, raise_cast_failure=True)
    328 
    329                 data = SingleBlockManager.from_array(data, index)

~/.pyenv/versions/3.8.3/envs/census/lib/python3.8/site-packages/pandas/core/construction.py in sanitize_array(data, index, dtype, copy, raise_cast_failure)
    490     elif subarr.ndim > 1:
    491         if isinstance(data, np.ndarray):
--> 492             raise Exception("Data must be 1-dimensional")
    493         else:
    494             subarr = com.asarray_tuplesafe(data, dtype=dtype)

Exception: Data must be 1-dimensional
```

#### Problem description

Yes, creating a series from an array is invalid. But the problem is that a bare `Exception` is raised for this. A different exception type like `ValueError` is expected. User code should [mostly] never be catching bare Exceptions, but may reasonable catch `ValueError`s or `TypeError`s from pandas routines.

I'm not entirely sure of the rationale for raising a bare Exception in the `sanitize_array` method, I started looking through the git blame but didn't go back that far.

I think a PR that just raises a `ValueError` in `sanitize_array` would be an appropriate fix and I can create that if given the thumbs up.

#### Expected Output

A `ValueError` is raised, that can be caught be user code.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : d9fff2792bf16178d4e450fe7384244e50635733
python           : 3.8.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 19.6.0
Version          : Darwin Kernel Version 19.6.0: Sun Jul  5 00:43:10 PDT 2020; root:xnu-6153.141.1~9/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.1.0
numpy            : 1.19.0
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.1.1
setuptools       : 49.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.16.1
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.0
fastparquet      : None
gcsfs            : None
matplotlib       : 3.3.0
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pyxlsb           : None
s3fs             : None
scipy            : 1.5.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
