2 Key Challenges of Streaming Data and How to Solve Them
Streaming data is flooding into companies; it’s coming from the web, social networks, clickstreams, sensors, Cloud, machines and devices — and the list goes on. The growing demand for faster analytics and customer insights have dramatically increased the growth of this type of data — and the need to extract business intelligence from it in real time. But there are challenges associated with collecting and using streaming data. We’ll take a closer look at some of those challenges and introduce a tool that will help.
In this article, we will dive into some of the challenges associated with streaming data. We will also introduce Talend Data Streams, an application that enables companies to solve those challenges, quickly and easily integrating real-time data streams into their data architecture.
1. Streaming Data is Very Complex
Streaming data is particularly challenging to handle because it is continuously generated by an array of sources and devices and is delivered in a wide variety of formats. There are relatively few developers that possess the skills and knowledge needed to work with streaming data, making it nearly impossible for companies give real-time access to those employees who are so eager to get their hands on it.
One prime example of just how complicated streaming data can be comes from the Internet of Things (IoT). With IoT devices, the data is always on; there is no start and no stop, it just keeps flowing. A typical batch processing approach doesn’t work with IoT data because of the continuous stream and the variety of data types it encompasses.
For instance, there can be hundreds of devices and sensors on a single wind turbine. Every device has a purpose: measuring oil level, the turbine’s position, the sway of the tower, the blade pressure, temperatures, etc. These devices are often produced by different manufacturers so the data can be quite different. This scenario of mixed devices and sensor data means the data schema can change unpredictably, potentially breaking data pipelines.
2. Business Wants Data, But IT Can’t Keep Up
The difficulties associated with integrating and accessing streaming data returns many companies to the much-maligned business and IT divide. The IT team is struggling to scale what they can do to provide data to the business team. The business team is in dire need of the data to solve business questions, get instant analytics, and find new business opportunities.
The problems occur when the business team, desperate to get their hands on the streaming data, bypass IT, and use any ad-hoc solution or approach that will get them to the data. The tools and processes the business people use to gain data access are outside of the normal IT protocol, resulting in unwanted new data silos and introducing a huge data governance risk.
Solution: Create Real-time Data Pipelines
For data-driven companies, the pitfalls surrounding streaming data are very real. The inundation of this type of data shows no signs of slowing, and the widening gap it is causing between business and IT is introducing new problems. To solve these challenges, Talend has introduced Talend Data Streams, a cloud-based, free application that can be obtained from the Amazon Web Services (AWS) Marketplace and can be up and running in minutes.
Win: Self-Service Streaming Data
Talend Data Streams makes streaming data integration faster and easier via a self-service web UI that is intuitive and accessible not only for data engineers, but for other data workers like data scientists and even some advanced data analysts and ad-hoc integrators.
Talend Data Streams combines the automation and deployment capabilities that companies need to achieve continuous integration with intuitive tools that can be adapted to fit unique needs.
Win: One Unified Interface
Streaming and batch pipelines can be designed in a single interface that is running on Apache Beam, a unified programming model that provides an abstraction layer for different run profiles, which is highly efficient and reliable. With Talend Data Streams, everything is treated as a stream, where streaming data comes with unbounded source, and batch data with bounded source.
Because Apache Beam supports multiple frameworks, the pipelines are highly portable. Instead of moving your data to work in one particular processing framework, the processing happens wherever the data is located, through Apache Beam to Apache Spark, Apache Flink, or Google Cloud Dataflow.
Win: Schema-on-Read
Talend Data Streams is built with schema-on-read capability, enabling auto-discovery of your data schema. The app can handle all the schemas all the time, and it can even patch through the columns it doesn't know, to only concern itself with the columns selected to use in scripting. This means any change in the source schema doesn’t negatively impact the real-time flow of data in the pipeline.
The Future of Streaming Data
Talend Data Streams will also be available as part of Talend Cloud, providing a truly collaborative platform across all kinds of data users with the Talend Cloud applications. The metadata, the data pipelines, and datasets are all shared across the platform.
Data experts, typically the analysts and data scientists, can use Data Streams to perform data ingestion and lightweight Extract, Transform and Load (ETL) processes without involving IT, while metadata is still captured. Data engineers can prepare the streaming data via the Talend Data Streams UI, and then embed data quality recipe from Talend Data Preparation in the pipeline and share the datasets across the platform — within hours, or minutes.
Talend Data Streams gives data engineers a sense of instant gratification with the unique Live Preview function that displays the status of data transformation every step of the way, this up-front, real-time view also helps reduce testing and debugging time. Companies can also leverage the Python component in Talend Data Streams to customize their transformation with Python coding or even existing scripts.
Currently the Talend Data Streams app is available as a single-user free application from the Amazon Marketplace. Stay tuned, because new features will be added to Talend Data Streams soon. The app will become commercially available as a Software as a Service (SaaS) that is a fully managed service via Talend Cloud. The vision of future versions will include more data preparation capabilities, and in-flight data quality checks on the data even before it hits the data lake to keep the quality high.
Related Links
- Get Talend Data Streams for free
- Getting Started with Talend Data Streams
More related articles
- Big Data and Agriculture: A Complete Guide
- Big Data and Privacy: What Companies Need to Know
- 5 Ways to Optimize Your Big Data
- Big Data for Supply Chain Management
- Big Data in Government
- Defining Big Data Analytics for the Cloud
- Big Data in Media and Telco: 6 Applications and Use Cases
- 7 Ways Big Data is Changing E-commerce
- How Big Data is Changing Healthcare
- Big Data for Small Business: A Complete Guide
- How Does Big Data Work for HR Analytics?
- What is Hadoop?
- What is MapReduce?
- What is Big Data? Free Guide and Definition
- Beginner’s Guide to Batch Processing
- An Intro to Apache Spark Partitioning
- What is Apache Spark?
- Big Data in Finance - Your Guide to Financial Data Analysis
- Talend Performance Tuning Strategy
- Stream Processing Defined
- Big Data in Marketing 101
- Big Data in Retail: Common Benefits and 7 Real-Life Examples