The energy and utilities industry is looking for advanced solutions to get actionable insights. The industry is undergoing major transformation with the advent of smart sensors, smart meters, and IoT-based technologies. The industry generates huge chunks of data from oil wells, utility grids, gas grids, smart grids, and other sensors. Terabytes of data is generated from structured as well as unstructured sources, which need to be analyzed and get real-time insights.
The industry is facing unprecedented challenges such as rising cost of operations, changing regulatory policies, environmental concerns, and increasing consumer expectations. Such challenges are driving these industries to adopt effective data management and data quality plans to gain significant insights and secure the market competitiveness, increase energy competitiveness, increase energy efficiency, manage risks, and lower operational cost. The deployment of the latest technologies such as Advanced Metering Infrastructure (AMI) and Supervisory Control and Data Acquisition (SCADA) systems is also helping to improve the amount and quality of data that the utilities sector has on supply and distribution.
Frequently Asked Questions
What is the expected CAGR for the Data Quality Software market?The overall data quality tools market is expected to grow at a CAGR of 17.7% from 2017 to 2022.
What is the purpose of deploying data quality solutions?Data quality software refers to a wide range of tools and services specifically designed to deliver comprehensive and precise data to organizations. Data quality software vendors offer a broad range of functions and capabilities, which include data cleansing, profiling, parsing, monitoring, and enrichment. The data quality software allow organizations to comprehend, standardize, and monitor the data over the course of its lifecycle, ensuring continuous operation within the system. Ensuring data quality should be a paramount concern to the authorities, as a good dataset within an organization can be a key enabler to gain competitive advantage in the market by conducting better analysis and craft business strategies that will have long-term implication on realizing organizational goals. The 6 key considerations of data quality, which every enterprise should seek for, include consistency, conformity, completeness, uniqueness, accuracy, and integrity of data.
Who would need to deploy Data Quality solutions?Data quality solution providers, Governance, Risk Management, and Compliance (GRC) solution providers, Consulting companies, Government agencies, Risk assessment service providers, Investors and venture capitalists, Value-added resellers, Small and Medium-Sized Enterprises (SMEs) and large enterprises, Third-party providers, Consultants/consultancies/advisory firms, Support and maintenance service providers and Technology providers etc.
What are the major application areas where Data Quality Tools prove to be effective?Data quality tools are generally effective in four areas: data cleansing, data integration, master data management, and metadata management. The tools generally identify errors with the help of algorithms and lookup tables. They also helps in managing multiple tasks, that include validating contact details and mailing addresses, data mapping, data consolidation associated with ETL tools, data validation reconciliation, sample testing, data analytics etc.