add OVERVIEW.md

Author: dimitri-yatsenko

OVERVIEW.md

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+# DataJoint Overview
+
+DataJoint is a library for interacting with scientific databases integrating computational dependencies as part of the data model. It is an ideal tool for team projects working on shared data-centric computational workflows.
+
+## Why use databases in scientific studies?
+
+Many scientists are reluctant to use databases due to their perceived unwieldiness, opting instead to use file repositories for managing their shared data. [Gray, 2005](https://arxiv.org/abs/cs/0502008)
+
+Yet databases provide several key advantages when it comes to sharing structured dynamic data:
+ 
+1. **Data structure:** databases communicate and enforce structure in data that reflects the logic of the scientific study.
+2. **Concurrent access:** databases support transactions to allow multiple agents to read and write the data concurrently.
+3. **Consistency and integrity:** database provide ways to ensure that data operations from multiple parties are combined correctly without loss, misidentification, or mismatches.
+4. **Queries:** Databases simplify and accelerate data queries -- functions on data to obtain precise slices of the data without needing to send the entire dataset for analysis. 
+
+## What does DataJoint bring?
+DataJoint solves several key problems for using databases effectively in scientific projects:
+
+1. **Complete relational data model:** database programming directly from a scientific computing language such as MATLAB and Python without the need for SQL. 
+2. **Data definition language:** to define tables and dependencies in simple and consistent ways.
+3. **Diagramming notation:** to visualize and navigate tables and dependencies.
+4. **Query language:** to create flexible and precise queries with only a few operators.
+5. **Serialization framework:** to store and retrieve numerical arrays and other data structures directly in the database.
+6. **Automated distributed computations:** computational dependencies 
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