According to IDC, the amount of newly generated data is expected to increase by 23% annually from 2020 to 2025, resulting in the creation of 175 ZB of data by 2025. To manage this huge amount of data, data engineers use a variety of data engineering tools, frameworks, and technologies.
In this article, we will discuss the 5 best data engineering tools in 2023.
Data engineering tools
Looker is a powerful data analytics and business intelligence (BI) software. It enables users to visualize, understand, and interpret data from a variety of sources. Here are some key features of this tool.
- Looker introduces an innovative LookML layer. It’s an innovative language for describing dimensions, aggregates, calculations, and relationships of data in an SQL database.
- Data engineers can easily create and customize data models. In this way, they can focus on the important aspects of analysis.
- It offers interactive data exploration tools. Using intuitive interfaces, users can discover relationships and trends.
- This tool empowers users to generate real-time reports, facilitating swift analysis of the most recent data. This capability enables informed, ongoing decision-making based on the latest insights.
- With an SQL-based interface, Looker makes it easy for data engineers to integrate with existing tools and applications.
- Non-technical employees can use company data without requiring advanced technical knowledge.
- Looker lets you make dashboards and reports that you can interact with and customize according to your needs.
Apache Spark is an extensive, open-source platform that simplifies the processing of large datasets. Here are some key features of this software.
- Apache Spark stands out for its ability to process data in memory. This makes operations on large data sets much faster.
- Moreover, Spark enables real-time data processing. It’s critical for apps needing immediate analysis and quick response to changing data.
- Spark is flexible, allowing you to work both in cluster mode and on various platforms such as Hadoop or Kubernetes.
- The software easily integrates with various data sources. It includes popular systems such as Hadoop, Apache Cassandra, Apache HBase, and Amazon S3. It, therefore, provides a wide range of data processing possibilities.
Tableau is one of the most respected data engineering tools in the field of big data and data engineering technologies. It has an intuitive interface that allows you to collect data from various sources via drag and drop. Here are the distinctive features of Tableau.
- Tableau swiftly handles large datasets, creating appealing visualizations without performance loss.
- The tool supports a variety of scripting languages like Python. It makes it flexible in solving various data analysis problems.
- With a simple drag-and-drop interface, Tableau is easy to understand. Thanks to this, data engineers can build reports and dashboards easily.
- The tool is scalable, which means it can be effectively adapted to different sizes and complexities of data sets.
Power BI is Microsoft’s business intelligence service. It aims to deliver interactive visualizations and business intelligence capabilities through an intuitive interface.
- Power BI enables data engineers to visualize and analyze data from various sources. It provides tools for data preparation, modeling, visualization, collaboration, and sharing.
- It stands out for its robust data visualization capabilities. It enables data engineers to create interactive reports and dashboards that can be accessed from anywhere and on any device.
- Power BI integrates seamlessly with a variety of Microsoft tools.
- This tool is user-friendly, making it easy to use even for people without extensive knowledge of BI software.
- What’s more, Power BI offers a free basic desktop version that you can use to create reports and dashboards.
- It can read and connect to data from Microsoft Excel and text files (such as XML and JSON). It can also collect data from BI tools such as Google Analytics, Facebook, and Salesforce.
- Power BI is accessible through a browser or offline on a desktop or mobile device.
SNOWFLAKE DATA WAREHOUSE
Snowflake is an innovative cloud data analysis and storage platform with a unique shared data architecture. Here are the key features of this software.
- Snowflake provides immediate flexibility. It allows users to adjust their data workloads independently of each other.
- It enables data engineers to store structured and semi-structured data, including formats such as JSON and XML.
- This software places a strong emphasis on data security. It is compliant with multiple security standards, including GDPR, HIPAA, PCI DSS, and SOC 1 and SOC 2.
- Snowflake is highly scalable. It allows users to create an almost infinite number of virtual data stores.
- Snowflake has a built-in automatic query optimization system.
Data engineering services play a key role in managing this huge amount of data. The article discusses the top five tools in 2023, such as Looker, Apache Spark, Tableau, Power BI, and Snowflake. Each of these tools offers unique features that enable data engineers to effectively manage and analyze data.