Frequently asked questions

Get answers to the most commonly asked questions about this product.

Augmented Data Explorer makes the process of searching and exploring across tables more interactive and makes running ad hoc analyses on data very simple. When a data scientist or business user needs to analyze unfamiliar data, Db2 Augmented Data Explorer can make this process much easier.

It connects to your Db2 database and processes natural language requests, returning real-time query results while a user is entering a query. These results are augmented with statistical insights that highlight what is important in the returned data.

You can download the beta version here. Sign in to your IBM account and download the zip file. Unzip the file and open the Readme for detailed instructions on running the install script. You must have Docker installed before you run the script.

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When a user crawls a database, Db2 Augmented Data Explorer analyzes a sample of the data to build a profile of metadata for the database tables, so that it can access this information while making real-time query recommendations.

Crawl process collects and calculates metadata such as table and column names, measurement level, unique categorical values, score indicating the relative usefulness of a column as a grouping column and a score indicating the relative likelihood of a column as the target of a statistical analysis.

After metadata crawling finishes, Db2 Augmented Data Explorer initializes a process called caching to store aggregated data and the statistical results derived from that data. Caching also happens when a user requests a specific query.

Caching can significantly improve response time, especially with slower connections and larger databases. Note that caching stores the analytical results of a query rather than the raw data. This method reduces the amount of storage needed and is optimized for display in Db2 Augmented Data Explorer.

The data is stored on an Elasticsearch index.

Db2 Augmented Data Explorer auto-builds a directed graph of the primary and foreign key relationships among the tables, usingpre-defined relations if available. If relationships are not defined, the tool uses the column names, data types and values to infer relationships between tables.

As a user types, Db2 Augmented Data Explorer converts the user's text into a query and uses the metadata to match the columns in this "proto-query" with columns that exist in the database. The tool suggests aggregations, groupings and conditions that can be applied based on the user’s search.

To protect your data, Db2 Augmented Data Explorer runs behind the firewall on your own network, so your data always stays on your network. It uses SSL for transmitting data from server to client.

Access is controlled via LDAP or in-app users. Once authenticated, users are authorized to different permission levels: search, crawl and administer. Users with crawl or admin permissions can create connections and crawl data. Users with search privileges can search all data that has been crawled.

IBM recommends crawling whenever the structure of your tables changes or new tables are added. If the database structure has changed (e.g., schema/table/column name changes), the tool could generate queries that no longer run against the database. It is recommended that you re-crawl in this case.

If data is added or changed, some of the cached results, such as aggregates, could be inaccurate. For some queries, the tool goes live to the database, so those results would remain good. You should re-crawl if your data has changed.

Db2 Augmented Data Explorer can also identify synonyms and concepts related to the text in the user’s query and augment an incomplete query with relevant matches.

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