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Blog Higher Education Industry

Seven Steps to Building a Data-Driven Culture in Higher Education

Seven Steps to Building a Data-Driven Culture in Higher Education

What we are hearing

At Datatelligent, we spend hours a day listening to all our customers in Higher Education. In the listening, we hear a lot of recurring concerns and themes. Here are just a few things we hear: 

  • “Traditionally, we’ve had strong student retention, but lately, it’s trending downwards, and we want to know why.”
  • “We want to know who our students are and find out the kind of students who succeed in our programs, but we don’t know where to start.”
  • “We need to identify at-risk students better and faster so we can get them the resources they need before it’s too late.”
  • “We like to say we’re an institution that makes data-informed decisions, but in reality, we don’t look at the data because we don’t have an easy way to look at data.”
  • “We need to simplify data visualization. We need dashboards that tell our people, ‘Here’s what you need to know.'”
  • “We know we have the answers in our data, and we talk about unifying data so we can build the analytics we need to understand our students, but we have systems everywhere, and we don’t have the big-dollar budget to integrate them.”

When we hear this, we know we’re talking to customers on the journey to building a data-driven culture at their institutions. They are experiencing growing pains. Being good listeners, the team here at Datatelligent wants to minimize the pain and speed up the growth.

Building a data-driven culture

We hosted a recent webinar with Debbie Phelps at Cowley College, Executive Director of Institutional Effectiveness and proud “office of one.”  Debbie explained how she, with limited resources, built a data-driven culture where they truly make data-informed decisions.

Debbie started with a plan and made Datatelligent a partner in their journey. Our team and our solutions played their part, but Debbie was the driving force behind the journey to being data-driven. Here’s how they did it.

1. leadership commitment and vision
  • Leadership Buy-in: Without this, the plan to build a data-driven culture goes nowhere. University leaders, including administrators, deans, and department heads, must champion the importance of data-informed decision-making. Their commitment sets the tone for the entire institution.
  • Vision Statement: Develop a clear vision statement that emphasizes the value of data-driven practices. Communicate this vision consistently to your team.
2. Infrastructure and data systems
  • Data Governance: Establish robust data governance practices. Define roles, responsibilities, and processes for data management. Ensure data security, privacy, and compliance. This takes a lot of work, but our customers, like Cowley College, who do this, see bottom-line lasting benefits and improve the success of their students – the real reason behind what we do.
  • Integrated Systems: Invest in systems that allow seamless data integration. Siloed data inhibits effective decision-making. This is where the Datatelligent Platform for Higher Education really helps you build your data-driven culture.
3. Data Literacy Training
  • Training Programs: So many institutions make the mistake of taking a “build it and they will come” approach. Not Cowley College, and not Datatelligent customers. We always advise and help you design regular workshops and training sessions on data literacy. Your team should understand basic statistical concepts, data visualization, and interpretation.
  • Department-Specific Training: Don’t forget to tailor training to specific roles (e.g., admissions, student services, finance). Each department has unique data needs.
4. Transparency and Communication
  • Transparency: This is an essential part of your governance and security plan. Also, make it a part of the training. Be patient about data sources, methodologies, and limitations. Your team should know where the data comes from and how it’s processed.
  • Regular Updates: This ensures everyone is on the same page in a data-driven culture. Provide timely updates on institutional performance metrics. Dashboards and reports should be accessible to all team members.
  • Feedback Loop: Just as Datatelligent listens to customers, as a data steward of your institution, it’s important to listen to your “customers.” Encourage your team to provide feedback on data quality and usability. Act on their insights.
5. Data-driven decision-making processes
  • Define Key Metrics: Key performance indicators (KPIs) relevant to each department. For admissions, it might be enrollment rates; for student services, retention rates; for advisement, identifying the students at risk and designing academic plans that ensure student success.
  • Use Cases: Illustrate real-world scenarios where good data and data visualizations influenced decisions. Share success stories to inspire everyone.
  • Cross-Functional Collaboration: Encourage collaboration across departments. Data insights often emerge at the intersection of disciplines. If you get the chance to talk to your peers at Cowley College, this is something they do well.
6. Ethical Considerations
  • Privacy and Consent: Your team should understand the ethical implications of handling student data. Ensure compliance with privacy laws (e.g., FERPA). This has remained constant, and hyper-vigilance is needed as AI tools are rolled out to enhance analytics.
  • Bias Awareness: Train your team to recognize and mitigate biases in data analysis. Ethical use of predictive models is critical, especially now that we have entered the age of AI, which, not surprisingly, mimics the same biases as its human counterparts.
7. Continuous Improvement
  • Assessment: Regularly assess the effectiveness of data-informed practices. Are we moving the needle on student retention? Are we identifying students at risk sooner? Are decisions improving? Is your team using data effectively?
  • Celebrate Wins: We encourage all our customers to do, acknowledge, and celebrate instances where data-informed decisions lead to positive outcomes. Recognize every team member’s contributions.
Conclusion

We have learned from our customers at Datatelligent that building a data-informed culture is a long but rewarding journey. It requires collaboration, adaptability, and a shared commitment to student success – the real motivation behind what we do. By empowering your team with data literacy and fostering a culture of curiosity, colleges, and universities can thrive in an increasingly data-driven world that will soon have jet-fueled added to the engines once AI tools catch up with the rest of us data-driven thinkers.

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Blog Human Services Industry

Data-Driven Innovation: A Dive into Datatelligent’s Impact on Tri-Town YMCA

Data-Driven Innovation: A Dive into Datatelligent's Impact on Tri-Town YMCA

In a recent interview on WGN Radio’s “Your Money Matters,” the spotlight shone on a groundbreaking partnership between Datatelligent and Tri-Town YMCA. The interview highlights the transformative power of data-driven innovation in community development.

Datatelligent, an active member of Innovation DuPage, has been at the forefront of leveraging data to drive positive change. The company’s collaboration with Tri-Town YMCA is a testament to the potential for innovation when technology meets community initiatives.

 

The interview delves into how Datatelligent’s expertise is being harnessed to enhance the efficiency and impact of Tri-Town YMCA’s programs. By employing data-driven insights, the YMCA aims to optimize resource allocation, improve program effectiveness, and ultimately better serve the community.

Tri-Town YMCA’s commitment to community development aligns seamlessly with Datatelligent’s mission to empower organizations through data. By integrating data analytics into their decision-making processes, the YMCA can:

  • better understand the community’s needs
  • identify areas for improvement
  • tailor their programs to make a more significant impact.

 

For an in-depth exploration of this exciting collaboration, listen to the full interview here. Gain insights into how data-driven innovation is shaping the future of community development. Learn how Datatelligent and Tri-Town YMCA are working together to create positive change.

 

Technology is playing a pivotal role in shaping our communities. Datatelligent’s collaboration with Tri-Town YMCA exemplifies the potential for data-driven innovation to drive positive social impact. This partnership is a beacon, showcasing how businesses and organizations can create a better, more informed future.

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AI Blog Higher Education Industry Snowflake

The Importance of AI-Powered Analytics in Higher Education

The Importance of AI-Powered Analytics in Higher Education

The future of AI is now

At Datatelligent, we look to the future for ways to help our customers solve decades-old Higher Education problems. We hear a lot of questions lately about AI and what it means for Institutional Research. Questions like, “How can Generative AI and Large Language Models help our analytics? Will adding AI extract the predictive insights we need to help students and help us with retention, recruitment, and funding?”

Well, it’s funny you should ask. On November 15, 2023, we are hosting a webinar on these very topics with our most AI-innovative partner, Snowflake. Elevate Education: AI Solutions for Higher Education.

Snowflake is moving fast, at Chicago-blizzard pace, embracing all that’s AI and announcing earlier this month, during Snowday, a host of new AI tools.  We will in turn innovate with our Higher Education customers and implement these tools into the Datatelligent Unified Data Platform.

The Definition of AI in Higher Education

AI-powered analytics is the use of artificial intelligence to analyze large datasets to identify patterns, trends, and insights. Here are some of the areas will innovate with AI-powered analytics with our higher education customers:

  • Student success: AI-powered analytics can be used to identify students who are at risk of dropping out or failing a course. This information can then be used to provide targeted interventions, such as tutoring or academic advising.
  • Student Recruitment and Enrollment: considered one of the holy grails of analytics, identify the best mix of students who will benefit and are succeed from the specialties offered by the institution. Closely related, AI can help identify so you can focus recruitment on the students that will help your institution win and retain their grant funding.
  • Enrollment Trends: Identifying the trends early that will impact future enrollment. Linking to all sorts of internal and external data sources, AI-powered insights helps plan for student recruitment in fast-changing demographics.
  • Faculty Planning: Recruitment doesn’t stop with students. AI can help with faculty planning, identifying the educational specialties that are in demand now and in the future. Recruitment efforts and education certifications can be planned years in advance.
  • Personalized learning: Personalized learning experiences can be created for students using insights from AI-powered data. This can be done by adapting course materials, providing individualized feedback, and recommending additional resources.
  • Administrative efficiency: Why not have that AI-bot be the helpful assistant it wants to be, automating scheduling, grading, and admissions processing? This can free up time for faculty and staff to focus on more strategic initiatives.
The Challenges of AI

Of course, AI is not the magic pill to make all our analytic and Institutional Research headaches go away. At Datatelligent, we help mitigate the challenges AI-powered analytics brings to higher education:

  • Data quality: AI-powered analytics immediately bring up Data Quality.  Institutions need to ensure the data is accurate, complete, and consistent, or your “insights” will be none of these.
  • Bias: AI algorithms can be biased, which can lead to unfair or inaccurate results. Data Analysts need to be aware of the potential for bias and make sure a human takes steps to mitigate it.
  • Ethics: The use of AI in higher education raises a number of ethical concerns, such as the potential for surveillance and discrimination. Institutions need to develop clear ethical guidelines for the use of AI in higher education. At Datatelligent, we have a well-developed AI Governance and Ethics framework.

Overall, AI-powered analytics has the potential to revolutionize higher education. As with any revolution there are always challenges, which is why it’s best to align with an ally before overthrowing any king. We’ll be talking about the AI Revolution on November 15. We hope to see you at the Datatelligent and Snowflake AI Solutions for Higher Education webinar.

Categories
Blog Food Assistance Human Services

How Food Banks Benefit from Partnerships

How Food Banks Benefit from Partnerships

How might your organization benefit?

As a food bank, food pantry, or food council, your mission likely involves reducing food insecurity or hunger and increasing access to healthy food. You probably ramped up during the pandemic and are still waiting for the need to decrease. You have likely already squeezed out every bit of efficiency in your operations with today’s tools.

But what if you could add a tool that, within three short months, can maximize the data collected in your various systems and communicate it effectively to stakeholders? Have you considered a partnership with Datatelligent and Tableau?

Datatelligent is a data analytics company that partners with nonprofit organizations to organize existing data. Conversely, Tableau is a leading data visualization tool that can transform complex data into easily understandable and actionable insights. Food banks, food pantries, food councils, and their human service partners have worked with us in many ways.

Data analysis and visualization

Organizations often input information about donors, volunteers, food types, needs, geography, expenses, and more into various software systems. Datatelligent pulls data from disparate systems and layers on Tableau’s data visualization tools. We transform this data into dashboards where various staff leaders can answer questions and make data-driven decisions through self-service.

Streamlined operations

Datatelligent can combine data sets that previously lived in data silos or even simple spreadsheets. Using data analytics, Food Banks and Pantries may identify bottlenecks or inefficiencies in their processes. With info from across their service area, Food Councils can visualize the trends in needs, resources, and gaps in the overall food assistance ecosystem. With the help of Datatelligent and Tableau, they can implement changes to streamline their operations, improve efficiency, and ultimately serve more people in need.

Improved fundraising and communications

How do you prove you are making a difference? Data analytics can help you identify donation trends, understand your donor base, and target communications. More importantly, effective use of data can help justify sustained or increased funding—especially when it illustrates how the services provided meet the need or highlights precisely who is most in need. Datatelligent and Tableau equip organizations with strategies that are more likely to resonate with donors and result in increased funding.

Contact us to learn how your Food Bank, Food Pantry, or Food Council can work with us. Tell the story of your food ecosystem and your organization’s impact. Consider partnering with Datatelligent and Tableau to take your organization to the next level.

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Blog Faith Member/Volunteer Engagement Outputs & Outcome

Religious Organizations Embrace Technology and Data Post Pandemic

Religious Organizations Embrace Technology and Data Post Pandemic

Faith-based organizations, like many other institutions, are increasingly relying on technology to accomplish their goals. From online worship services to digital giving platforms, thriving congregations and ministries have been quick to adopt new technologies to meet the needs of their communities.

The pandemic spurred changes in attendance from online and outside service attendance in the spring of 2020 to a hybrid of in-person and online attendance in 2022. The Pew Research Center documented the changes through five surveys between July 2020 through November 2022. Virtual viewing of services online or on TV increased, in-person attendance declined, and overall participation remained nearly steady with a slight decline since the pandemic.[1]

While attendance may have been tracked by religious organizations before, deeper analysis can help leaders understand which programs are most popular—whether in-person or virtual–and for whom. Virtual attendance creates opportunities and challenges to meet a new definition of the sense of “community” religious institutions seek to create. Heidi Campbell, professor of communication at Texas A&M University, stated, “Digital technology in the church and in ministry is here to stay. And our future is definitely hybrid.”[2]

One of the most significant changes that religious organizations have experienced in recent years is the integration of data into their operations. The Pew Research confirms what congregations may observe anecdotally in the demographic differences of attendees by participation type. By using data analysis tools, congregations, and ministries are gaining insights into their members’ needs and preferences, which allows them to better tailor their programs and services.

Faith-based organizations are also turning to social media and technology to improve their outreach efforts. By engaging with their communities on social media, organizations can spread their message to a wider audience and engage with individuals who may not be able to attend in-person events or who joined the virtual religious community. They can use social media analytics to understand which posts are most effective and how to better engage with their followers. Others are using virtual reality technology to give members a virtual tour of their facilities or to provide a more immersive worship experience.

It’s important to note that while technology can certainly be a valuable tool for faith-based organizations, it is not a replacement for the personal connections and relationships that are at the heart of congregations and ministries. However, by embracing new technologies and integrating data into their operations, religious-based organizations can better understand and meet the needs of their communities.

_________________________________
[1] Pew Research Center, March 2023, “How the Pandemic has Affected Attendance at U.S. Religious Services,” by Justin Nortey and Michael Rotolo, and accessible at https://www.pewresearch.org/religion/2023/03/28/how-the-pandemic-has-affected-attendance-at-u-s-religious-services/.
 
[2] Council on Foreign Relations (CFR), “Religion and Technology Webinar” held March 23, 2023, and accessible at https://www.cfr.org/event/religion-and-foreign-policy-webinar-religion-and-technology. In this webinar, Heidi A. Campbell, professor of communication at Texas A&M University, and Paul Brandeis Raushenbush, president and CEO of Interfaith Alliance, discuss the meeting of religion and digital culture, and its effect on religious communities. Carla Anne Robbins, senior fellow at CFR, moderates.
Categories
Blog Faith Member/Volunteer Engagement Outputs & Outcome Snowflake Tableau

Empowering Faith-Based Organizations with Data: How Tableau and Snowflake can Increase Data Maturity

Empowering Faith-Based Organizations with Data: How Tableau and Snowflake can Increase Data Maturity

Faith-based organizations play a significant role in communities all around the world. These organizations have unique challenges when it comes to data management and analysis, as they often rely on volunteers and need more resources. However, modern tools such as Tableau and Snowflake can help faith-based organizations increase their data maturity and make more informed decisions.

Tableau is a data visualization tool that allows organizations to create interactive and engaging data visualizations. On the other hand, Snowflake is a cloud-based data warehouse that provides a secure and scalable platform for storing and analyzing data. Faith-based organizations can use these tools together to gain insights into their operations and make data-driven decisions.

Here are a few ways that faith-based organizations can use Tableau and Snowflake to increase their data maturity:

  1. Track and analyze donations: One of the most critical aspects of any faith-based organization is donations. With Tableau and Snowflake, organizations can track and analyze donations over time to understand trends and patterns. They can create dashboards that show how much money they have received, where it came from, and how it was used. This can help them make more informed decisions about fundraising and budgeting.
  2. Monitor participation: Faith-based organizations rely on attendance and engagement to gauge the effectiveness of their programs. With Tableau and Snowflake, organizations can track attendance and engagement metrics over time. They can create dashboards that show how many people attended each event, how engaged they were, and how long they stayed. This can help them identify which programs are most effective and where they need to make improvements.
  3. Monitor volunteer engagement: Volunteers are a critical part of many faith-based organizations, and it can be challenging to track their recruitment, training, assignments, and recognition. Tableau and Snowflake can help organizations evaluate volunteer performance by tracking hours worked, tasks completed, and opportunities for volunteer training or recognition. Data-driven volunteer management helps direct attention to the volunteers who might need additional support.
  4. Analyze program effectiveness: Faith-based organizations run a variety of programs, from education and outreach to charity and support services. With Tableau and Snowflake, organizations can analyze the effectiveness of these programs by tracking metrics such as program attendance, participant feedback, and outcomes for service recipients. This can help organizations identify which programs are most effective and where to improve.
  5. Monitor and improve operations: Like any organization, faith-based organizations have operational challenges that can be difficult to manage. With Tableau and Snowflake, organizations can track operational metrics such as budget, staff time, and inventory. They can create dashboards that show how these metrics change over time, identify areas of concern, and make data-driven decisions to improve operations.

Tableau and Snowflake are powerful tools that can help faith-based organizations increase their data maturity and make more informed decisions. Faith-based organizations can gain insights into their operations and make data-driven decisions by tracking donations, attendance, volunteer performance, program effectiveness, and operational metrics. With the right tools and strategies, faith-based organizations can use data to improve their programs and services and positively impact their communities.

Categories
Blog Human Services Member/Volunteer Engagement

How Food Banks and Pantries Can Tackle SNAP Benefit Expiration

How Food Banks and Pantries Can Tackle SNAP Benefit Expiration

In the wake of the COVID-19 pandemic, food insecurity has become a critical issue in many communities worldwide. Food banks and food pantries have played a vital role in providing essential support to those who are struggling to make ends meet. However, with the expiration of COVID-related SNAP (Supplemental Nutrition Assistance Program) benefits and the rise of inflation, food banks and food pantries are facing new challenges. This blog will explore how food banks and food pantries can overcome these challenges.

1. Collaborate Locally

Collaborating with local businesses and farms can be an effective way for food banks and food pantries to supplement their supply of fresh produce and other food items. Some businesses and farms have excess inventory, unsold products, or needed items that they can donate to food banks and food pantries in their own communities. By forging partnerships with these organizations, food banks, and food pantries can enhance their supply of nutritious food for their clients.

2. Strengthen Inventory Management

Effective inventory management is critical for food banks and food pantries to prevent food waste and ensure that clients receive fresh and nutritious food and necessities. By implementing inventory management practices, food banks and food pantries can monitor the shelf life of their food items, prioritize items that are nearing expiration, and track most-in-need items by time of month and year.

3. Leverage Technology

Incorporating technology can be a game-changer for food banks and food pantries. By implementing various software, food banks and food pantries can monitor their inventory, volunteers, and donations in real time. This can help them decide which projects to prioritize and increase efficiency.

4. Educate the Community

Educating the community about food insecurity and the role of food banks and pantries can help raise awareness and encourage donations. While everyone is affected by inflation, many need to be aware of SNAP benefits’ limitations, such as not covering soap, diapers, hygiene products, or ready-to-eat items. By partnering with local schools and community organizations, food banks and food pantries can organize educational workshops and events to educate the community about food insecurity and how they can help.

Food banks and food pantries face new challenges due to COVID-related SNAP benefit expiration and inflation. However, by collaborating with local businesses and farms, strengthening effective inventory management, leveraging technology, and educating the community, food banks and food pantries can overcome these challenges and continue to provide essential support to those in need.

Categories
Blog Data Maturity Other

From Data Awareness to Data-Driven Excellence: Datatelligent’s Data Maturity Model for Organizational Success

From Data Awareness to Data-Driven Excellence: Datatelligent’s Data Maturity Model for Organizational Success

In today’s data-driven world, organizations need to harness the power of data to gain insights, make informed decisions, and stay competitive. However, not all organizations are at the same level of data maturity. Some may struggle with basic data management, while others may have advanced analytics capabilities but lack a data-driven culture.

This is where Datatelligent comes in. We assist organizations in assessing their data maturity and developing a roadmap for improvement. We have developed a data maturity model with four stages, each with specific characteristics and pain points.

Let’s take a closer look at each data maturity stage and how Datatelligent can help organizations overcome challenges and move towards becoming data-driven.

  1. Data Aware: In the Data Aware stage, organizations have basic data awareness but lack a systematic approach to data management. Data is often ad hoc, siloed, and not used for decision-making purposes.

    Datatelligent can help organizations in this stage by providing data management and organization solutions to create a solid foundation for data-driven decision-making. This may include implementing data governance practices, data quality assessment, and data integration strategies to ensure that data is organized, standardized, and easily accessible for analysis.

  2. Data Proficient: In the Data Proficient stage, organizations have standardized reporting on a reporting platform, but data is primarily used for awareness purposes and not consistently utilized for decision-making.

    Datatelligent can assist organizations in this stage by providing advanced analytics and reporting solutions, empowering them to leverage data for informed decision-making. This may involve implementing advanced analytics techniques such as data visualization, data exploration, and predictive analytics to uncover insights and drive data-informed decision-making.

  3. Data Savvy: In the Data Savvy stage, organizations have started using data to make some business decisions, but data usage is inconsistent and often restricted to certain departments or silos.

    Datatelligent can help organizations in this stage by implementing data governance frameworks, data democratization strategies, and providing training and support to ensure data is used effectively across the organization. This may include developing data governance policies, establishing data sharing protocols, and providing training programs to build data literacy and skills across the organization.

  4. Data Driven: In the Data Driven stage, organizations have embraced data-first thinking, where data is embedded into all business and decision-making processes. All systems and people work together to make the most effective and efficient use of data.

    Datatelligent can partner with organizations in this stage by providing advanced analytics solutions, developing predictive models, and enabling data-driven culture and practices throughout the organization. This may involve fostering a culture of data-driven decision-making through change management and leadership support.

We understand that every organization’s data maturity journey is unique, and our team of experienced data analysts and consultants is dedicated to helping organizations overcome barriers and unlock the full potential of their data. We provide tailored solutions that align with the specific needs and goals of organizations, guiding them towards becoming data-driven organizations.

Contact Datatelligent today to learn more about how we can assist your organization on its data maturity journey.

Categories
Blog Data Maturity Other

Unlocking the Power of Data: How to Become a Data-Driven, Data Mature Organization

Unlocking the Power of Data: How to Become a Data-Driven, Data Mature Organization

Data is the lifeblood of successful organizations, and becoming data-driven is essential for thriving in today’s business landscape! Embracing data as a strategic asset can unlock unprecedented opportunities for growth and innovation. Here are some key steps to becoming a data-driven organization.

Step 1: Define Clear Data Goals
The first step in becoming a data-driven organization is to define clear data goals. What do you want to achieve with data? Identify the key objectives, such as improving decision-making, enhancing customer experience, optimizing operations, or driving revenue growth. By setting specific and measurable data goals, you can align your data initiatives with your organization’s overall strategy and vision.

Step 2: Establish Data Governance
Data governance is the foundation of any successful data-driven organization. It involves creating robust policies and procedures to ensure data quality, integrity, and security. Define roles and responsibilities for data management, access, and usage. Establish data standards and guidelines to ensure consistency and accuracy in data collection, storage, and analysis. Implement data governance practices that align with your organization’s needs, industry regulations, and best practices.

Step 3: Invest in Data Infrastructure
Having the right data infrastructure is crucial for becoming a data-driven organization. Invest in modern data management tools and technologies that enable efficient data collection, storage, analysis, and visualization. Choose solutions that align with your organization’s data goals, scalability requirements, and budget. Consider cloud-based solutions for flexibility, scalability, and cost-effectiveness. Ensure that your data infrastructure is scalable, secure, and capable of handling large volumes of data to support your organization’s data-driven initiatives.

Step 4: Foster a Data-Driven Culture
Building a data-driven culture is critical for becoming a data-driven organization. It involves creating a mindset where data is valued and data-driven decision-making is ingrained in the organization’s DNA. Provide training and resources to help employees become data-literate and capable of using data for decision-making. Encourage a collaborative approach where employees are encouraged to share data insights, learn from data, and use data to drive innovation and continuous improvement.

Step 5: Enable Data-Driven Decision-Making
Data-driven decision-making is at the heart of a data-driven organization. Use data to drive insights, inform decision-making, and measure performance. Encourage data-driven experimentation, where data insights rather than gut instincts back decisions. Implement data-driven processes and workflows to ensure that data is used consistently across the organization. Foster a culture of curiosity and learning, where employees are encouraged to explore data, ask questions, and make data-driven decisions at all levels of the organization.

Step 6: Learn from Data
Becoming a data-driven organization requires continuous learning and improvement. Leverage data insights to iterate and optimize strategies, processes, and outcomes. Use data to identify patterns, trends, and opportunities for improvement. Implement a feedback loop where data insights are used to refine strategies and drive continuous improvement. Encourage a culture of data-driven innovation, where data is used to identify new business opportunities, optimize operations, and drive growth.

Becoming a data-driven organization is a journey that requires effort, commitment, and a strong leadership vision. By following the key steps outlined in this blog post, organizations can unlock the power of data and leverage it to drive growth, innovation, and success. Here at Datatelligent, we work with customers to help them embrace data as a strategic asset, establish robust data governance, invest in modern data infrastructure, foster a data-driven culture, enable data-driven decision-making, and embrace continuous learning from data. By taking the first step to becoming data mature, your organization can thrive in today’s data-driven world and achieve industry gain.

Categories
Blog Other Solution Engines Solution Previews

4 Key Differences of Datatelligent’s Subscription-based Approach to Data Analytics

4 Key Differences of Datatelligent's Subscription-based Approach to Data Analytics

Are you looking for a new and different approach to data analytics?

Datatelligent provides a more flexible and cost-effective way for organizations to access the data and insights needed to make better business decisions. Our subscription-based approach to data analytics is different from traditional, one-time purchase software licensing models.

Below are four key differences of our data analytics subscription.

  1. Scalability: Our subscription-based DAaaS services are designed to be easily scalable, allowing organizations to adjust the size and scope of their analytics needs as their business needs change. This can help ensure that organizations have access to the right data and tools at the right time without incurring additional costs for unnecessary capacity.
  2. Updates and Maintenance: Our subscription-based service include regular updates and maintenance, ensuring that the data analytics tools and technologies remain up-to-date and functional. This can help organizations avoid the cost and hassle of maintaining their on-premise infrastructure and ensure they always have access to the latest analytics capabilities.
  3. Access to Expertise: By partnering with Datatelligent, organizations gain access to a team of data analytic experts, and our Data Literacy subscription helps organizations improve their data literacy.
  4. Cost Structure: A subscription-based approach typically involves paying a recurring fee over a set period of time (e.g., monthly, quarterly, or annually) rather than a considerable upfront cost. This can make data analytics more accessible to organizations with limited budgets and allows for better cost management and planning.

Datatelligent’s Subscriptions

For our clients, Datatelligent provides three DAaaS subscriptions (Solutions, Data Operations, and Data Literacy).

  • Solutions Subscription: Analytic Solutions for your entire organization & data solutions to bring together all your sources, including:
    • Analytic Solution Engines
    • Data Solution Engines
    • Unified data platform
    • Data maturity roadmap
  • Data Operations Subscription: Data analytics operations managed all in one place, including:
    • Data capacity services
    • Project flex-up services
  • Data Literacy Subscription: Education and enablement as well as solution adoption to ensure successful knowledge transfer

Our Solutions, Data Operations, and Data Literacy subscriptions are powered by Tableau, Snowflake, Power BI, Cloud Infrastructure, Stitch, FiveTran, and many others.

Contact Datatelligent to learn more about how our unique Data Analytics as a Service subscription service can help you make informed decisions.

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