Data automation describes using software tools to process data to create a data pipeline instead of using manual methods.
Why is Data Automation Important?
Data is the lifeblood of modern business. Every customer interaction and almost every operation creates data. This data is used to inform decisions that carry the business forward. Automating the journey the data takes to become information that provides insights is the key to delivering the real-time insights that make a company responsive to the needs of customers and the market.
A business generates and gathers so much data that without automation, it would quickly become impossible to avoid overwhelming manual data processing resources.
The Evolution of Data Automation
Before the emergence of data integration solutions, IT departments and software developers coded applications to process data and created scripts to tie together their custom code. This cumbersome approach was quite fragile, so it consumed vast resources to keep it running.
Over time, a market emerged for data extraction, transformation, and loading (ETL) and data preparation software that removed the need for hand coding with reusable components. These data pipelines became pervasive enough to require their own orchestration and centralized management, leading to more comprehensive data integration solutions to scale the automation further, imposing further data administration overheads while eliminating custom code.
Modern data management solutions such as the Actian Data Platform provide an end-to-end solution that extracts data from operational sources, transforms it into a form suitable for analysis and connects that data in a data warehouse to a business intelligence (BI) solution.
Automating the Journey from Raw Data to Actionable Analytics
To get the most value from operational data, it has to be converted into a form that is easy to analyze. This transformation is a multistep process that requires many steps to automate. Below are some examples of the steps taken in this journey.
Connecting to Operational Data Sources
Once the required systems of record are identified, the data has to be extracted from them. These sources can include social media feeds, website log files, customer relationship management (CRM) and enterprise resource planning (ERP) systems. Data integration technology comes with pre-built connectors to most data sources.
Data Extraction
Data can be extracted from its source with custom scripts, ETL tools, or application programming interfaces (APIs) such as Apache SPARK.
Data Filtering
Data pipelines can consume a lot of storage and computing resources, so it makes sense to filter out irrelevant or unnecessary records, fields and outlying values to improve data quality and provide more accurate analytics.
Merging Data
When merging two data files, a rules-based approach ensures duplicate records are not created. Reconciliation rules help merge data when two records with the same key must be combined.
Filling Gaps
When using data to train a machine learning model, ensuring it is not too sparse is important. Missing values can be replaced using default values.
Data Transformation
Data transformation changes the format of data to improve its consistency. Transformations can be as simple as bucketing values, rounding or changing the data type to improve analysis.
Data Loading
To support effective analysis, data needs to be loaded into a database designed for data analysis, such as the Actian Vector columnar database.
Data Reporting and Visualization
Typically, the final step in a data automation process is populating tiles on a business intelligence (BI) dashboard with insights derived from the accumulated operational data. These dashboards enable informed decision making in real time.
Orchestrating Data Automation
Data Integration tools such as Actian DataConnect provide the visual tools to construct an automated data pipeline and centralized management of workflows to keep administration costs down.
The Benefits of Data Automation
The benefits of data automation include:
- Having the latest insights readily available provides the business with the visibility it needs to respond rapidly to changing customer behavior and market dynamics.
- Automation allows an organization to best use all of its data assets.
- A unified data automation platform lets a business scale data pipelines without overwhelming limited IT resources.
Data Automation With the Actian Data Platform
The Actian Data Platform provides a unified location to build and maintain all data automation and analytics projects. The built-in data integration makes building and managing data pipelines easy. DataConnect provides connectors to hundreds of data sources and all Business Intelligence solutions. The integrated Vector analytics database uses vectorized queries and columnar storage to provide the greatest performance with the minimum tuning.
Data can be stored on-premise and across multiple public clouds, including AWS, Azure and Google Cloud Platform. Support is provided for distributed queries and block storage so database instances can be configured in line with the characteristics of the workload.
