Data Orchestration Basics: How to Organize Data to Gain Real-Time Insights
Data orchestration automates the organization and transformation of siled data, increasing data accessibility and visibility. Pohan Lin, senior web marketing and localizations manager, Databricks, discusses how businesses can operationalize data to make more accurate, real-time business decisions by providing increased value and actionability.
What Is Data Orchestration?
Data orchestration is the automated process of managing data to reduce silos between data sources and storage locations. Data orchestration platforms take data from multiple sources, clean, organize, and combine the data, and then send it to storage locations for data analysis.
Why Is Data Orchestration Important?
The more data we possess, the more successful our attempts at bringing about positive, large-scale change. Leveraging the analytics gathered from big data enables the optimization of day-to-day operations. It also supports the improved intelligence of different types of neural networks and AI algorithms and drives the success of data-driven business decisions.
The problem? The more data we possess, the more dark data, data silos, and governance issues emerge.
Despite 99% of businesses actively investing in big data strategies, a Newvantage survey reports that only 24% have created a data-driven organization. Only 48.5% of companies are driving innovation with data, and 39% are succeeding in managing data as a business asset.
Dates from Newvantage Partners
As data volumes and customer demands increase, businesses struggle to keep up. The tendency to deploy data analytics and Bi tools on an ad-hoc, department-level basis plays an integral role in why big data strategies are so prone to overwhelm, especially if deployed under continuous integration (CI) and deployment techniques.
However, for the businesses that successfully create data-driven organizations, 96.4% report that the investment yielded significant results. Real-time insights and improved internal processes are just two benefits of data orchestration deployment.
See More: Cloud Orchestration Vs. Cloud Automation: How Do They Benefit Your Business?
The Steps of Data Orchestration
The exact process of data orchestration varies between systems, but the common goal is to aggregate siled data to improve data accessibility, visibility, and analysis. Therefore, the data orchestration process falls into four key stages.
- Data Collection and Organization
Before structuring your data, it needs to be collected and organized. Data orchestration tools use SDKs and APIs to collect all the existing data and incoming data from your business’ customer touchpoints and cloud storage platform. This data undergoes a thorough organization process, including labeling and integrity-checking, before it’s ready for the next stage.
- Data Transformation
To increase accessibility and speed up the data analysis, orchestration tools transform data into one singular format or language. Take dates, for example, which can take multiple different formats. Where one system might format the date as May 24, 2022, another might format it as 05/24/2022 or 05/24/22.
Disparities are arduous to sort manually and can result in errors that compromise data quality. Orchestration tools automate this while streamlining task management, unifying data from different sources into internally compatible formats for quick and accurate data analysis.
- Data Unification
Now that your data is internally compatible, it can be stitched together to create a unified view of your customer.
Rather than leave your website, app, and other touchpoint data to exist as separate parts, orchestration tools unify this data to create intricately individual customer personas. You can make better marketing and sales decisions based on observable customer interactions with an overarching view of your customers’ behavior as they journey across touchpoints.
Data unification also applies to other data forms, like images or languages. For example, convolutional neural network filters identify patterns present in images.
- Data Activation
Activation involves making accumulated data available to the tools that use it, such as your analytics platforms or business intelligence tools. With no required data loading, professionals can access data on their chosen platforms as and when needed. Eliminating data silos and dark data is a crucial benefit of data orchestration
Unstructured, disorganized, and siled data slows down business operations. Data collection, organization, and flow direction must be handled manually by data scientists, giving them less time to analyze and utilize the data.
Cleaning and organizing data take up a substantial 60% of data scientists’ time, followed by data collection, which takes up 19%.
There’s also the risk of human error. Coupled with the over-accumulation of dark data, data errors decrease visible data’s quality (and, in turn, value). This can lead to fatal errors that wreak havoc on internal operations and decisions.
It is by far the only reason you should invest in data orchestration. Let’s discuss some of data orchestration’s other benefits.
Data Privacy Compliance
GDPR and CCPA compliance are currently hot topics as recent research shows that 90% of US businesses are ill-equipped for CCPA compliance. Data privacy laws like GDPR and the CCPA ensure customer data’s ethical collection and storage. If your company’s data is disorganized or unstructured, proving compliance becomes more difficult.
Oversights, such as failing to delete data after a lawful amount of time, are also a massive compliance risk that can be avoided by using automated orchestration tools.
Removing Data Bottlenecks
A data bottleneck refers to a point in a business system where data flow is so restricted that it halts or ceases entirely. It often occurs when there isn’t enough data handling capacity to control high traffic levels.
Say you have an unorchestrated data ecosystem and want to access data from an unfamiliar warehouse. You’ll need to request the data from a specialized expert to avoid fatal errors. Your request will join a long queue (as you’re probably not the only one asking for data), and you also have to allow time for manual data transformation and unification.
By automating this process, orchestration tools significantly minimize data acquisition times.
Improving Data Governance
Your data governance strategy guides the standards and policies that determine the usability and integrity of your data. An unorchestrated data ecosystem will have trouble governing data because of the disparity of its data pipeline.
Orchestration eases and enriches the governing process, increasing organizational visibility to facilitate accurate governance implementations.
Acquiring the Freshest Customer Data
Unorchestrated ecosystems can not keep up with the fast-paced fluidity of changing consumer demands, behaviors, and trends. You can get immediate access to the most up-to-date customer insights by leveraging automated orchestration.
Once a customer calls into your VoIP contact center, clicks on your email CTA, or browses a page on your website, data orchestration tools ensure that this data is collected, transformed, and activated for widespread business use.
Also, because your customer data can be consolidated into unified customer profiles, you can spend less time on data interpretation and more time operationalizing the data to bolster your customer-centric strategies.
Your business needs an intricately structured data ecosystem to provide customers with the personalized, omnichannel experiences they crave. Manual orchestration isn’t viable with data volumes increasing as customer demands rise.
To avoid silos, dark data, and other stresses, turn to data orchestration tools. Data orchestration makes your data more valuable by increasing its accessibility, accuracy, and actionability, allowing you to make more intelligent business decisions.
What data orchestration tools are you using? Share with us on LinkedIn† Twitter† or facebook† We’d love to know!
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