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For leaders of large nonprofits, it's crucial to build a data-driven culture. The world of grant funding is fiercely competitive. Securing resources hinges on a data-driven approach that goes beyond basic program evaluation. The steps below can help you get started! 🔷 Invest in Data Infrastructure: Ensure your organization has the tools it needs to collect, store, and analyze data effectively. This might involve a Customer Relationship Management (CRM) system, data analytics software, or cloud-based solutions. 🔷 Build a Data-Savvy Team: Assemble a team with expertise in data analysis and interpretation. Consider hiring a data analyst or partnering with a data consulting firm to bridge any skill gaps. 🔷 Establish a Data Governance Framework: Develop clear policies and procedures for data collection, storage, and access. This ensures data integrity and compliance with relevant regulations. 🔷 Encourage open communication about data and empower staff to utilize data for continuous improvement. Read more about this important topic over on our blog! https://lnkd.in/eiFaPJaj #KindallEvolve #NonProfit #DataDriven

HOW TO ASSIGN DATA STEWARDS IN AN ORGANISATION? After attending numerous #DataGovernance conferences and engaging in 1on1 conversations with experts, I've gained valuable insights. (Thanks to DataQG community).   🍀 Companies often face challenges hiring full-time #DataSteward roles, especially at the beginning of their Data Governance program. Primarily due to budget constraints, prioritization of value delivery, and a lack of clearly defined processes and roles.   Typically, organizations opt to assign Data Steward responsibilities to existing employees, with or without incentives. However, this approach can create a negative perception, as employees may feel burdened with added responsibilities without more time or financial support.   🍀 With these observations, I've formulated a set of steps for assigning Data Stewards. My objective is to seek advice from fellow experts to refine and enhance this process. Thanks in advance 😍   1️⃣ #Observation and #Identification: ·       Observe how data is commonly used within your organization and identify the person who is normally responsible for addressing data issues and solving the issues. ·       Try to keep it simple as much as possible to not overwhelm people, avoiding the title "Data Steward" until the role is dedicated 100%. 2️⃣ #Simplification and #Communication: ·       Start with basic responsibilities, emphasizing their importance in regular communication. ·       Establish a #DataCommunity rather than focusing solely on a #DataStewardCommunity. ·       Encourage discussions in meetings about whom to contact for data issues and foster collaborative problem-solving. 3️⃣ Alignment with #OrganizationalGoals: ·       Ensure that assigned responsibilities align with the broader goals of the organization, the vision for the next 5-10 years to start build the base from today. ·       Emphasizing the strategic importance of data stewardship. 4️⃣ Tool Provision and #Training: ·       Don’t forget to provide the necessary tools for stewardship responsibilities and offer training. ·       Keep processes as simple as possible, and actively listen to and address any difficulties. 5️⃣ Continuous #Communication: ·       Regularly check in to address concerns, gather feedback, and celebrate successes. 6️⃣ #MetricsforSuccess: ·       Establish key performance indicators (#KPIs) or metrics to measure the success of the data stewardship program. ·       Include metrics such as improvements in data quality, efficiency in issue resolution, and overall data literacy within the organization. 7️⃣ #Adaptability: ·       Be prepared to adapt the approach based on the evolving needs of the organization. ·       Adapt until it is effective yet simple to follow for current and future onboarding members. 8️⃣ Gradual Expansion and Formalization: ·       Over 1-2 years, gradually expand responsibilities. ·       Eventually, formally designate individuals as Data Stewards and transition them into the role fulltime.

Historical Data Once upon a time, in a world driven by technological advancements, there was a diligent data analyst named Alex. They had a unique role in the information and technology support team, harnessing the power of data to unlock valuable insights and optimize the support process. Every day, Alex collected, processed, and analyzed large volumes of data, derived from various sources within the organization. This data held the key to understanding the performance, efficiency, and effectiveness of the support team's operations. Alex meticulously organized the data, transforming it into meaningful metrics and visualizations. With their arsenal of visualizations and analytics tools, Alex painted a vivid picture of the support team's strengths and weaknesses. They identified trends, patterns, and anomalies, shedding light on critical areas that required attention. The deep dive into data empowered the team leaders to make informed decisions and prioritize their efforts accordingly. By analyzing historical data, Alex was able to forecast future demand for support services, enabling the team to proactively allocate resources and staff members. This predictive analysis helped prevent potential crises and ensured swift assistance to those in need. Alex's work fostered a culture of efficiency and a proactive approach within the support team. Furthermore, Alex's role extended beyond analyzing day-to-day operations. They collaborated with the development team, providing valuable insights into product performance and user feedback. This enabled the developers to make data-driven improvements to their products, addressing customer pain points and enhancing user experience. As time went on, the impact of Alex's work became evident throughout the organization. Support response times decreased, customer satisfaction soared, and operational costs were optimized. The entire company recognized the value of Alex's role as a data analyst, acknowledging the crucial connection between data analysis and the success of the information and technology support team. In this story, Alex exemplifies the indispensable role of a data analyst in information and technology support. Their ability to analyze and interpret data transforms raw information into actionable insights, driving operational improvements and strategic decision-making. With their expertise, Alex ensures that technology support thrives in a data-driven world, becoming a catalyst for success and growth. I am a data analyst #informationandtechnologysupport #technology #innovation #dataanalyst #jobseeker #hirethisman #recruiters

A new guide: The accessibility data analyst. As I've talked to teams around the world I've seen that it doesn't matter what precise job titles people have — what matters is the roles we carry out. The data analyst role might be a program manager, a project admin or a hard core developer nerd on paper. What matters is their ability tell the story of inclusion through data. #accessibility #a11y

THE UNSUNG HEROES IN DATA MANAGEMENT When we talk about Data Management, we often overlook Data Capturers. Many dismiss data capturing as a mundane task and belong to the back office. But, let us shine the spotlight on Data Capturers today! They are the unsung heroes in the management of data. INCONSISTENT DATA Picture this, a business has inconsistent data that is full of errors. In this scenario, business owners will find that they are navigating a ship without a compass. Accurate data capturing is the compass guiding a business toward success. WHAT ARE THE SKILLS & AND RESPONSIBILITIES OF DATA CAPTURERS? Here are some of the skills that data capturers must have: Attention To Detail Data Entry Proficiency Speed And Accuracy Problem-Solving Skills Technical Aptitude Security and Awareness Organised The above list could easily have more added on. Follow me, as my future posts will unpack the skills on the list, and what they entail. “Data Capturing: Where Data Magic Begins!” #sunnyvirtualsolutions  #smallbusinesssupport #virtualassistant  

𝐎𝐯𝐞𝐫𝐜𝐨𝐦𝐢𝐧𝐠 𝐑𝐞𝐬𝐢𝐬𝐭𝐚𝐧𝐜𝐞: 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬 𝐟𝐨𝐫 𝐒𝐮𝐜𝐜𝐞𝐬𝐬𝐟𝐮𝐥 𝐃𝐚𝐭𝐚 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 Implementing a data governance project within an organization can be a transformative endeavor, promising improved data quality, compliance, and decision-making. However, it's not uncommon for such initiatives to encounter resistance and conflicts along the way. From concerns about data ownership to fears of change, various factors can impede progress. To ensure the success of a data governance project, organizations must proactively address these challenges and foster a culture that embraces the value of data governance. Here are some strategies to remove conflicts and resistance to change: 🪡Communicate the Purpose and Benefits 🪡Engage Stakeholders Early and Often 🪡Address Concerns About Data Ownership and Control 🪡Provide Training and Support 🪡Demonstrate Quick Wins and Value 🪡Address Cultural Barriers 🪡Establish Clear Policies and Guidelines 🪡Empower Champions and Advocates 🪡Monitor Progress and Adapt 🪡Celebrate Success and Sustain Momentum 𝑪𝒐𝒎𝒑𝒍𝒆𝒕𝒆 𝒂𝒓𝒕𝒊𝒄𝒍𝒆: https://lnkd.in/gTWdJSTG If your organization needs help overcoming resistance to implement data governance, DM me the word 𝐇𝐄𝐋𝐏! I will send you an example of the output from one of our 𝐅𝐑𝐄𝐄 1 hour strategy sessions👏🏼 ---------- ✍🏼 I'd ❤️ to 👂🏼 your thoughts below. 💡Please repost and share with your network. 🔔Follow Fox Consulting for content like this 𝐎𝐍𝐋𝐘. ✔️Follow Cher Fox (The Datanista), CDMP for content like this, newsletters, reposts of high quality relevant content, jobs, and support for job seekers. ---------- #businessintelligence #dataanalytics #datasecurity #datagovernance #datastrategy #datainitiatives #datawarehouse #datamanagement #testautomation #dataquality

#data entry # management #organisation "Understanding Data Entry: The Backbone of Information Management" "Demystifying Data Entry: What It Is and Why It Matters in Business" "Data Entry Explained: Processes, Roles, and Significance in Modern Organizations" "The Power of Data Entry: Transforming Raw Information into Actionable Insights" "Data Entry 101: A Comprehensive Guide to the Basics and Beyond" "Why Data Entry is Essential for Businesses: Unlocking the Value of Organized Information" "The Role of Data Entry in Decision-Making: How Accurate Data Drives Smart Choices" "Data Entry: The Key to Unlocking Operational Efficiency and Effectiveness" "Data Entry: Bridging the Gap Between Information Collection and Analysis" "Data Entry and Beyond: Exploring Its Evolution in the Digital Age"

🌟 Importance of Data Integrity: Ensuring Accurate & Reliable Data 🌟 As a data analyst, financial analyst, and business analyst, I understand firsthand the crucial role that data integrity plays in driving informed decision-making and achieving business success. Data integrity refers to the accuracy, consistency, and reliability of data throughout its lifecycle, from collection to analysis and reporting. Here's why it's so vital and some best practices for maintaining it: 1️⃣ Foundation of Informed Decisions: Accurate and reliable data forms the foundation upon which strategic decisions are made. Whether it's analyzing market trends, assessing financial performance, or optimizing business processes, trustworthy data is essential for driving actionable insights. 2️⃣ Building Trust: In today's data-driven world, trust is paramount. Stakeholders, clients, and investors rely on data to make critical decisions. By ensuring data integrity, we instill confidence in our analyses and recommendations, fostering trust and credibility within our organizations and beyond. 3️⃣ Risk Mitigation: Inaccurate or inconsistent data can lead to costly errors and misinformed decisions. By maintaining data integrity, we mitigate the risk of making flawed assumptions or taking misguided actions, ultimately safeguarding business interests and reputation. Here are some best practices for ensuring data integrity: 🔍 Data Validation: Implement robust validation checks during data collection to detect and prevent errors at the source. 🛡️ Access Controls: Restrict access to data and implement security measures to prevent unauthorized alterations or tampering. 🔄 Data Quality Checks: Regularly perform data quality assessments and audits to identify and address discrepancies or inconsistencies. 🔒 Data Governance: Establish clear policies, procedures, and responsibilities for data management to ensure accountability and compliance. 🔧 Automated Processes: Utilize automation tools and workflows to streamline data entry, processing, and validation, reducing the risk of human error. As professionals in the field of data and financial analysis, it's incumbent upon us to uphold the highest standards of data integrity. By adopting these best practices, we not only ensure the accuracy and reliability of our analyses but also contribute to the overall success and credibility of our organizations. Let's continue to champion data integrity as a cornerstone of excellence in our work! #DataIntegrity #DataAnalysis #FinancialAnalysis #BusinessAnalysis #DataQuality #DataManagement

Do you search for a job? Do you want to do something relevant that has policy implications and impacts society at large? Consider applying for the open position below.   Data spaces are distributed systems,  implemented by one or more infrastructures and a governance framework that enables secure and trustworthy data transactions between participants. The European Union invests in establishing domain-specific data spaces (health, industry, agriculture, finance, mobility, Green Deal, energy, public sector and skills), and the Data Space Support Centre (DSSC) defines a common set of rules and policies for these data spaces. Sooner or later, organizations and individuals can join data spaces in their role of data users, providers, or other roles, to exchange data with other data space participants and co-create value in innovative ways. Your job would be to operationalize human-centricity in a data space context - what technological components, business, legal and regulatory aspects, and governance decisions ensure the human-centric design and operation of data spaces? If you have an analytical mind and good communication and writing skills, you are in an excellent position to be the human-centric data space architect within DSSC. More information can be found below.

Do you feel you spend too much time on market data admin and not enough time driving value? 😱   You are not alone - many teams managing market data do!   The administration and management of market data subscriptions requires precious staff attention and time ⏱ that could be more fruitfully spent on higher-value projects. 📈   Often, the business wants to do more innovative things with data to get a competitive edge.   Focus on more important activities that drive true value:   ☑ Building strategic vendor and stakeholder relationships ☑ Proactively consult with the business on new data requirements ☑ Build understanding of the market and vendor product pipeline ☑ Quickly bring together the right solutions that quickly drive value ☑ Invest in strategic sourcing and develop a strategic roadmap ☑ Become valued, trusted advisors to business partners   For this to happen you need to free up highly skilled team members from the burden of market data admin.   But how? Easier said than done! Right?   Curious to learn what you / your team members are doing to ease that admin burden⁉ Or fully buried and in the need of additional help❓ Either way, let me know in the comments below... 📣   #marketdata #marketdatamanagement #admin #costmanagement #managedservices   TRG Screen