message: Extra information in README and center logo
diff: +<div align="center">
  <img src="https://duckdb.org/images/DuckDB_Logo_dl.png" height="50">
  +</div>
  +<p>&nbsp;</p>
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  +</p>
  +## DuckDB
  +DuckDB is a high-performance analytical database system. It is designed to be fast, reliable and easy to use. DuckDB provides a rich SQL dialect, with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs), and more. For more information on the goals of DuckDB, please refer to [the Why DuckDB page on our website](https://duckdb.org/docs/why_duckdb.html).
  ## Installation
  -If you just want to install and use DuckDB, please see [our website](https://www.duckdb.org) for installation and usage instructions.
  +If you want to install and use DuckDB, please see [our website](https://www.duckdb.org) for installation and usage instructions.
  +
  +## Data Import
  +For CSV files and Parquet files, data import is as simple as referencing the file in the FROM clause:
  +
  +```sql
  +SELECT * FROM 'myfile.csv';
  +SELECT * FROM 'myfile.parquet';
  +```
  +
  +Refer to our [Data Import](https://duckdb.org/docs/data/overview) section for more information.
  +
  +## SQL Reference
  +The [website](https://duckdb.org/docs/sql/introduction) contains a reference of functions and SQL constructs available in DuckDB.
  ## Development
  For development, DuckDB requires [CMake](https://cmake.org), Python3 and a `C++11` compliant compiler. Run `make` in the root directory to compile the sources. For development, use `make debug` to build a non-optimized debug version. You should run `make unit` and `make allunit` to verify that your version works properly after making changes. To test performance, you can run several standard benchmarks from the root directory by executing `./build/release/benchmark/benchmark_runner`.
  