Governance Archives - gettectonic.com - Page 7
Quest to be Data-Driven

Quest to be Data-Driven

“Data-driven” is a business term that refers to the utilization of data to inform or enhance processes, decision making, and even the revenue model. The quest to be data-driven is afoot. In recent years, a data-driven business approach has gained a great deal of traction. It is true that every business deals with data — however, data-driven businesses systematically and methodically use data to power business decisions. Incorporating the notion of being a data-driven enterprise enriches the understanding of how data can profoundly impact business operations. Leveraging data not only offers valuable insights but also enhances adaptability, thereby sharpening the competitive edge of an organization. These insights serve as a foundation for making market predictions and adapting business strategies accordingly, often leading to revenue growth. While data may not provide solutions to all organizational challenges, embracing a data-driven approach lays a solid groundwork for achieving organizational goals. Data-driven contrasts with decision making that may be driven by emotions, external pressure, or instinct. So, what exactly constitutes a data-driven enterprise? It transcends mere number-crunching; it involves creating sustainable value for customers and innovating efficiently in the digital economy. Encouraging a data-driven approach across all facets of the business is paramount to success. Gaining data insights from data is invaluable. It allows organizations to reshape customer interactions, provided the data is accurate, accessible, and integrated into existing processes. However, many struggle to extract value from their data due to the complexity of transforming raw data into actionable insights. Understanding the hierarchy of data, information, and insights is crucial, as actionable insights drive data-driven success. Furthermore, adaptability emerges as a crucial factor in today’s rapidly evolving landscape. The ability to swiftly respond to changes and leverage data for informed decision-making is paramount. Data-driven insights serve as powerful tools for facilitating change and fostering agility, ensuring organizations remain competitive. Moreover, data serves as a catalyst for revenue generation through various business models such as Data as a Service (DaaS), Information as a Service (IaaS), and Answer as a Service (AaaS). By putting customer satisfaction at the forefront and leveraging data-driven insights, organizations can evolve their products proactively and drive growth. Building a data-driven enterprise involves a strategic approach encompassing nine key steps, including defining end goals, setting tangible KPIs, and fostering a data-driven culture across the organization. However, challenges such as deciding what to track, lack of tools or time for data collation, and turning data into meaningful insights may arise. Overcoming these challenges requires a cultural shift towards data-driven decision-making and the adoption of modern data architectures. Walking (or perhaps running) the data-driven journey with Tectonic involves connecting and integrating various data sources to ensure seamless data flow. By embracing a data-driven approach, organizations can unlock the full potential of their data, driving innovation, enhancing customer experiences, and achieving long-term success in today’s dynamic, rapidly evolving business landscape. Expanding upon this foundation, let’s go deeper into the transformative power of data-driven enterprises across various industry sectors. Consider, for instance, the retail industry, where data-driven insights revolutionize customer experiences and optimize operational efficiency. In the retail sector, understanding consumer behavior and preferences iscrucial to daily, quarterly, and annual success. By harnessing data analytics, retailers can analyze purchasing patterns, demographic information, and social media interactions to tailor marketing strategies and product offerings. For example, through personalized recommendations based on past purchases and browsing history, retailers can enhance customer engagement and drive sales. Moreover, data-driven insights enable retailers to optimize inventory management and supply chain operations. By analyzing historical sales data and demand forecasts, retailers can anticipate fluctuations in demand, minimize stockouts, and reduce excess inventory. This not only improves operational efficiency but also enhances customer satisfaction by ensuring products are readily available when needed. Furthermore, in the healthcare industry, data-driven approaches revolutionize patient care and treatment outcomes. Electronic health records (EHRs) and medical imaging technologies generate vast amounts of data, providing healthcare professionals with valuable insights into patient health and treatment efficacy. By leveraging predictive analytics and machine learning algorithms, healthcare providers can identify patients at risk of developing chronic conditions, enabling early intervention and preventive care. Additionally, data-driven approaches facilitate personalized treatment plans tailored to each patient’s unique medical history, genetic makeup, and lifestyle factors, improving treatment outcomes and patient satisfaction. In the manufacturing sector, data-driven strategies optimize production processes, enhance product quality, and reduce operational costs. By implementing Internet of Things (IoT) sensors and connected devices on the factory floor, manufacturers can collect real-time data on equipment performance, energy consumption, and production efficiency. Analyzing this data enables manufacturers to identify inefficiencies, minimize downtime, and proactively schedule maintenance to prevent costly equipment failures. Moreover, data-driven insights inform process improvements and product innovations, enabling manufacturers to stay competitive in an increasingly globalized market. The ultimately transformative impact of data-driven enterprises extends across various industry sectors, revolutionizing business operations, enhancing customer experiences, and driving innovation. By embracing a data-driven approach and leveraging advanced analytics technologies, organizations can unlock new opportunities for growth, efficiency, and competitive advantage in today’s data-loaded digital economy. Becoming data-driven requires harnessing the full potential of your data, transforming it into actionable insights, and iteratively refining your processes. Remember, data itself is not the ultimate goal but rather a powerful tool to drive informed decision-making and organizational growth. To establish a truly data-driven organization, consider the following nine steps: By following these steps, your organization can effectively harness the power of data to drive innovation, improve decision-making, and achieve sustainable growth in today’s data-driven landscape. Tectonic recognizes the challenges in the quest to be data-driven. We’ve launched a Data Cloud Salesforce Implementation Solution to help you. Content updated May 2024. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing,

Read More
public sector and tribal governent

What is BI in Salesforce?

Salesforce BI helps to create fast, digestible reports to help you make informed decisions at the right time. Salesforce Einstein is a leading business intelligence software solution that will help streamline your operations. Read on in this insight to learn how Salesforce BI capabilities including Tableau rank in the Gartner Magic Quadrant. Make the right decision every time using analytics that go beyond business intelligence software. See why Gartner named Salesforce (Tableau) a Leader in the Gartner® Magic Quadrant™ for Analytics and Business Intelligence Platforms for the 11th consecutive year. Data and analytics leaders must use analytics and BI platforms to support the needs of IT, analysts, consumers and data scientists. While integration with cloud ecosystems and business applications is a key selection requirement, buyers also need platforms to support openness and interoperability. Analytics and business intelligence (ABI) platforms enable less technical users, including business people, to model, analyze, explore, share and manage data, and collaborate and share findings, enabled by IT and augmented by artificial intelligence (AI). For several years, the Magic Quadrant for Analytic and Business Intelligence Platforms has emphasized visual self-service for end users augmented by AI to deliver automated insights. While this remains a significant use case, the ABI platform market will increasingly need to focus on the needs of the analytic content consumer and business decision makers. To achieve this, automated insights must be relevant in context of a user’s goals, actions and workflow. Many platforms are adding capabilities for users to easily compose low-code or no-code automation workflows and applications. This blend of capabilities is helping to expand the vision for analytics beyond simply delivering datasets and presenting dashboards. Today’s ABI platforms can deliver enriched contextualized insights, refocus attention on decision-making processes and ultimately take actions that will deliver business value. In addition to the increasing consumer design focus trend, we see other key market trends, including the need for improved governance of analytic content creation and dissemination, and the demand for a headless, open architecture. For example, a headless ABI platform would decouple the metrics store from the front-end presentation layer, enabling more interoperability with competitive products. ABI platform functionality includes the following 12 critical capabilities, which have been updated to reflect areas of market change, differentiation and customer demand: Gartner added three new critical capabilities as part of our metrics store evaluation criteria this year:  ABI platforms have always been about measurement. For decades, the slicing and dicing of measures by their dimensional attributes was synonymous with the act of performing business intelligence. However, over the last decade, the focus on metrics and measurement was overshadowed by data visualization. As data visualization became the most conspicuous capability, some business executives began to conflate ABI platforms with data visualization — as if ABI platforms are glorified chart wizards. This misconception minimizes much of the work performed and the business value delivered by ABI platforms. Establishing metrics stores as a critical capability to execute makes it clear that defining and communicating performance measures throughout an organization is one of the key purposes of an ABI platform. Analytics collaboration is a combination of many features (such as Slack/Teams integration, action frameworks) that collectively improve an organization’s ability to make decisions with consensus. Data science integration reflects the increasing likelihood that a business analyst may want to use data science to test certain hypotheses, and that data scientists will need to leverage features such as data prep and data visualization. In addition, Gartner is changing “catalogs” to “analytic catalogs” to emphasize a set of requirements that are not being met by ABI platform vendors today. Most large enterprises have thousands of reports built across multiple ABI platforms, but consumers in these organizations have no easy way to access these reports. The name change to analytic catalogs reflects the need for ABI platform vendors to deliver analytic content with the consumer in mind. Three critical capabilities were removed from our evaluation criteria: security, natural language generation (NLG; rolled into data storytelling) and cloud analytics (which will no longer be considered a platform capability, but instead a go-to-market strategy covered in the Magic Quadrant). And one of the security sub-criteria, about the granularity of authorization (e.g., row-based security) has been moved to the enterprise reporting capability. Salesforce (Tableau) Tableau, a Salesforce company, is a Leader in this Magic Quadrant. Its products are mainly focused on visual-based exploration that enables business users to access, prepare, analyze and present findings in their data. CRM Analytics, formerly Tableau CRM, provides augmented analytics capabilities for analysts and citizen data scientists. Tableau has global operations and serves clients of all sizes. In 2022, Tableau reinforced its augmented consumer vision to provide contextualized insights with deeper integration with Salesforce Data Cloud. IT also improved decision intelligence by bringing domain-aware insights into action with Revenue Intelligence and other Salesforce-native apps. The extensible design and x-platform integrations (Salesforce Flow, MuleSoft, UiPath and Looker) further enable composable analytics to bring insights into workflow with agility. Strengths Cautions Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

Read More
Salesforce Data Studio

Salesforce Data Studio

Data Studio Overview Salesforce Data Studio is Salesforce’s premier solution for audience discovery, data acquisition, and data provisioning, offering access to the world’s largest premium data ecosystem. It provides: Data Studio is a self-service platform that connects data owners and buyers directly, fostering new opportunities for audience discovery, sharing, and activation. Leading brands like Anheuser-Busch, Conagra, Essence, and Heineken leverage Salesforce Data Studio to enhance the value of their data and drive revenue. Announcing Salesforce Data Studio Salesforce Data Studio addresses the shortcomings of traditional data exchanges and marketplaces. Unlike legacy platforms that rely on intermediaries, Data Studio allows data owners to maintain control and transparency. The platform ensures secure transactions with comprehensive data governance tools, enabling precise control over data access, usage, and duration. Key Features of Salesforce Data Studio: Industry Reactions Salesforce Marketing Cloud: The Leader in Digital Marketing Salesforce Marketing Cloud enables marketers to deliver connected, personalized, and real-time consumer engagement across all channels globally. With Marketing Cloud Einstein, marketers can harness artificial intelligence to optimize timing, channel, content, and audience for their marketing messages. Brands like Dunkin’ Donuts and Nestle Waters rely on Marketing Cloud to enhance engagement and advance their business goals. On average, companies using Marketing Cloud see a 27% increase in campaign effectiveness and a 26% boost in marketing ROI. Pricing and Availability Salesforce Data Studio is available now in several editions: The new Audience Discovery and Search feature will be available starting November 2017. Like Related Posts Salesforce OEM AppExchange Expanding its reach beyond CRM, Salesforce.com has launched a new service called AppExchange OEM Edition, aimed at non-CRM service providers. Read more The Salesforce Story In Marc Benioff’s own words How did salesforce.com grow from a start up in a rented apartment into the world’s Read more Salesforce Jigsaw Salesforce.com, a prominent figure in cloud computing, has finalized a deal to acquire Jigsaw, a wiki-style business contact database, for Read more Service Cloud with AI-Driven Intelligence Salesforce Enhances Service Cloud with AI-Driven Intelligence Engine Data science and analytics are rapidly becoming standard features in enterprise applications, Read more

Read More
gettectonic.com