Data integration: A catalyst for transformation in the energy sector
Imagine walking into the office on a hectic day seeking answers about potential pipeline risks and perhaps needing to visualize oil wells in 3D in your lead field office. There were some discrepancies regarding key oil distribution processes and flow rates. However, you couldn’t view the issues since the data was murky. Despite the reports from various components about your infrastructure and workflows, you lacked the tools and high-level view needed to make sense of it. It then that you realize it is time for your company to invest in data integration and make its data assets more powerful!
Integrating data is an essential part of the overall data management process. Data integration aims to create a unified set of information by combining data from multiple sources and systems. The goal of data integration is to create a clean, consistent set of data that meets the information needs of a variety of end-users and organizations. Using it, companies can gather relevant data from multiple sources on a single platform and see the business performance in real-time. In implementing the integration, it is crucial to understand what types of data need to be gathered and analyzed, where each type of data comes from, how the system uses the data, what types of analyses need to be performed, and what report types need to be updated.
The energy industry needs data integration, especially as new technologies such as AI, IoT, edge computing, etc., are getting integrated to power this sector. Integrating smart meters, smart grids, synchrophasor, and real-time weather prediction systems with big data facilitates dispatch decisions, improves efficiency, organizes inventory, and increases reliability.
Benefits of data integration for the energy industry:
- Bringing disparate datasets together
Today, data is knowledge in our data-driven world.
Imagine your analysts manually scraping every one of your oil fields for data and then entering it into various databases and spreadsheets for further analysis! The ability of energy companies to perform cross-functional analytics is constrained due to data silos, complex tools, and monolithic architectures. Leaders must invest in an “intelligent data integration foundation to overcome these barriers.
Integrating data from disparate sources into a single dataset offers users consistent access to data and delivery of data from across the spectrum of subject areas and structure types. It meets the information needs of all applications and business processes. Through data integration techniques, disparate data sources can be effectively aggregated into a unified view.
An example is using data from CRM systems in conjunction with ERP systems. This enables an organization to be more efficient and prevents data loss during processes such as billing.
- Builds artificial intelligence and analytics-ready data
An integration process brings together data from disparate sources to create a meaningful and value-added data set for analytics and business intelligence. Examples of integration processes include extract, transform, and load (ETL), data replication, and virtualization. ELT targets data lakes, which can house huge amounts of structured and unstructured data or a cloud data warehouse. A method like this is ideal for supporting artificial intelligence (AI), machine learning, predictive analytics, and real-time data applications.
According to the latest report by Technavio, the global artificial intelligence in the energy market is expected to grow by USD 8.06 billion during 2020-2024, at a CAGR of almost 48%. Data integration and visual analytics are driving the global artificial intelligence market in energy.
Artificial Intelligence facilitates real-time analysis for effective decision-making by synthesizing data in real-time. With the ongoing decarbonization, decentralization, and digitalization of the energy sector, Data Analytics (AI) has become increasingly important. Pull factors, such as the advent of affordable and more accessible technology, as well as advances in computer power, have made more data available and opened new possibilities for analysis. Meanwhile, push factors, such as an increasing share of renewables in electricity generation and a growing number of active actors in the electricity system, increase complexity and raise the need for data analytics.
In addition to delivering analytics insights when needed, modern data integration solutions make it easy to handle, merge, reconcile and continuously access updated data.
- Effortless and risk-free
Collaboration is easier and effortless when easy accessibility is available! When data is shared among internal teams and applications or between organizations, integrated data becomes more valuable as more people can be involved and can use it effectively.
Establishing connections has traditionally been a painful task that took a long time, sometimes even months. Manually coding point-to-point integrations is not only time-consuming but also risky. Especially in an age of globalization, it is impossible to wait even weeks to connect two data sources.
Cloud data integration is the new trend. iPaaS is fast and easy due to the preexisting adapters and connectors and designed to simplify even complex B2B integrations: mapping has been simplified, and the integration architects can work with different data formats and standards.
Cloud technology facilitates data integration; how?
The cloud data integration process entails using tools and technologies to connect multiple applications, systems, repositories, and IT environments. This helps in facilitating data and processes exchange in real-time.
With cloud data integration, complex data integration tasks can be easily processed, and modern workloads can be deployed and managed by leveraging high performance and reliability. Cloud data integration allows companies to overcome integration challenges by connecting legacy systems and cloud applications via APIs. In fact, by 2025, the global integration platform as a service (iPaaS) market is expected to reach $10.3 billion. Considering that iPaaS offers are at the heart of cloud data integration, this data isn’t surprising.
Public and private cloud platforms have mature tools for integrating data. For instance, data integration is easy for energy companies with Azure Data Factory, a fully managed, serverless data integration service. Visually integrate more than 90 data sources with maintenance-free connectors included at no additional cost. Code-free ETL and ELT processes can be created in an intuitive environment, or enterprises can write their own.
The first step towards powerful data integration is to move your data to the cloud.
Moving on-premises data into the cloud is the first and most challenging step in cloud migrations. Thanks to Microsoft’s Azure File Migration Program, the process is easier than ever before. By sponsoring the use of Data Dynamics’ StorageX, organizations can now migrate their data into Azure at no extra cost and with no separate migration licensing.
StorageX is Data Dynamics’ leading unstructured data management solution that delivers policy-based data management with no vendor lock-in. Through this program, Microsoft and Data Dynamics aim to help organizations address some of their most critical challenges in the cloud migration lifecycle, such as cost, speed, talent, and risk. Customers can register their migration project information with Data Dynamics and start moving data today.
Begin your journey to the cloud with Data Dynamics and Microsoft; leverage intelligent, compliant, policy-based, zero-cost migrations into Azure. To know more, visit www.datadynamicsinc.com/microsoft or Contact us at email@example.com.You can also join our upcoming webinar to learn about StorageX and the Azure File Migration Program on 24th February 2022 at 11:00 AM EST. Topic: ‘Migrate your data to Azure like a boss with StorageX at Zero Cost.’ Click here to register for the webinar.