How data teams can do more with fewer resources

New data tools and technologies can help your team get more done with less budget, headcount and risk.
August 30, 2022

In today’s economic climate of furloughs, layoffs and restructuring, flexibility and resilience are increasingly critical. To stay afloat, businesses of all sizes are struggling to do more with less. When it comes to data — data storage, data integration, data analytics projects and so on — your team could probably be doing quite a bit more with limited or even shrinking resources.

Data leaders can take advantage of new tools and opportunities to reduce the manual effort and time involved in data projects and decrease time to market — while more effectively answering not only the questions they know, but the questions they haven’t yet thought to ask! 

In the current economy, no one can predict what will happen next, but you can reduce your dependence on external resources and free up team bandwidth. Here are some ways to expand your capabilities and drive business growth while running lean.

Automate wherever possible

One of the most effective ways to reduce inter-team dependence is to automate wherever possible. This increases resilience, reliability and integrity. The automation could be in anything: ingesting data automatically from your data sources to your central data destination, employing automatic data massages and transformations, automating business intelligence dashboards, and so on.

In a world of changing data sources and APIs — and rising data demands — you shouldn’t have to maintain, manage or host DIY solutions. 

Automation also tends to reduce costs, as resources used to manage various data activities can be reallocated elsewhere.

Take advantage of prebuilt, scalable resources

Utilizing prebuilt, scalable resources for your data initiatives means you don’t have to build them yourself. Is there already an easy way of getting your data to your destination? Are there transformation scripts for your use case?

With the time and effort saved, you and your team can focus on higher-value analytics. You’ll also have the ability to deliver new data projects right away, including combined information from existing and new sources.

And with prebuilt and managed resources, your maintenance, hosting and management costs may be minimal or negligible, because you can pay flexibly, increasing spend gradually as your business grows.

Leverage data security initiatives to expand self-serve analytics

With the COVID lockdowns, physical access to places and people was limited; organizations had to undertake data democratization initiatives in a world of hybrid work and distributed workforces. Across the globe, businesses were forced to put new digital safeguards in place. Role-based access control (RBAC), along with end-to-end encryption and multi-cloud to comply with data residency requirements, became critically important to ensure data integrity, availability, accuracy and confidentiality. (If you’re wondering how to comply with data residency and related requirements, take a look at our recent guide, which walks you through common definitions and compliance options.)

These data safeguards allowed organizations to continue business operations on a global scale without compromising data security or compliance — and more secure data access opened the door to self-service analytics, which freed up data teams to focus on more advanced projects, as opposed to basic reporting.

Consider how you can leverage data security initiatives to expand data democratization and self-serve analytics. That should enable your data team to do more without additional resources or headcount.

Re-evaluate your data strategy

While trying to provide business users reliable access to data and insights, ask yourself: What are our bottlenecks, and could they become enablers? If you think the answer is yes, you’re probably right.

Let’s take a quick look at two examples.

Resources

Executing any type of data project requires resources: budget, time, expertise, etc. Planning and brainstorming about how to secure those resources for a given data project is a bottleneck for many organizations — and that’s particularly true in a pandemic or unpredictable economy. 

However, leveraging prebuilt, scalable resources and automating wherever possible can turn a lack of resources into an enabler, as your team can now operate effectively with less budget and less bandwidth.

Outdated services

Recent advances in data technology mean you can often serve customers better with fewer resources and less risk. Ask yourself whether new tools would allow you to complete projects with less time, effort, resources and risk:

  • How could you expand and diversify the services you use?
  • Could you ingest customer data alongside your own data to provide them insights?
  • Could you unlock historical analysis within your data sources?
  • Is there a way to anonymize data as it enters a destination? 

These are just a few questions you could be asking yourself regularly. If your current platform or service isn’t able to help you innovate and better serve customers over time, consider addressing that in a way that helps you turn bottlenecks into enablers.

Consider automated ELT

In uncertain markets, businesses invest in data to clarify their business vision and identify their requirements to generate impact, improve customer retention rates and outperform the competition.

At Fivetran, our mission is to make data access as simple and reliable as electricity — and to allow your data team to do more with limited resources by eliminating your data engineering overhead. We offer over 200 fully managed, automated data connectors that you can set up in minutes. 

If you’re wondering whether you can save time or money by building the data pipelines yourself, we highly recommend “Build vs. Buy Data Integration,” which walks you through the basic calculations involved in comparing prebuilt and DIY data integration solutions. (Spoiler alert: Building data pipelines yourself almost always costs more.)

Check out our customer case studies for detailed examples of how we’ve helped data teams more efficiently serve stakeholders across departments — including in marketing, finance, sales and customer success analytics.

You can also sign up for our 14-day free trial to see how easy we make it to get your data from source to destination — with no coding required and a thoughtful ERD for every SaaS source.

Start for free

Join the thousands of companies using Fivetran to centralize and transform their data.

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How data teams can do more with fewer resources

August 30, 2022
How data teams can do more with fewer resources
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New data tools and technologies can help your team get more done with less budget, headcount and risk.

In today’s economic climate of furloughs, layoffs and restructuring, flexibility and resilience are increasingly critical. To stay afloat, businesses of all sizes are struggling to do more with less. When it comes to data — data storage, data integration, data analytics projects and so on — your team could probably be doing quite a bit more with limited or even shrinking resources.

Data leaders can take advantage of new tools and opportunities to reduce the manual effort and time involved in data projects and decrease time to market — while more effectively answering not only the questions they know, but the questions they haven’t yet thought to ask! 

In the current economy, no one can predict what will happen next, but you can reduce your dependence on external resources and free up team bandwidth. Here are some ways to expand your capabilities and drive business growth while running lean.

Automate wherever possible

One of the most effective ways to reduce inter-team dependence is to automate wherever possible. This increases resilience, reliability and integrity. The automation could be in anything: ingesting data automatically from your data sources to your central data destination, employing automatic data massages and transformations, automating business intelligence dashboards, and so on.

In a world of changing data sources and APIs — and rising data demands — you shouldn’t have to maintain, manage or host DIY solutions. 

Automation also tends to reduce costs, as resources used to manage various data activities can be reallocated elsewhere.

Take advantage of prebuilt, scalable resources

Utilizing prebuilt, scalable resources for your data initiatives means you don’t have to build them yourself. Is there already an easy way of getting your data to your destination? Are there transformation scripts for your use case?

With the time and effort saved, you and your team can focus on higher-value analytics. You’ll also have the ability to deliver new data projects right away, including combined information from existing and new sources.

And with prebuilt and managed resources, your maintenance, hosting and management costs may be minimal or negligible, because you can pay flexibly, increasing spend gradually as your business grows.

Leverage data security initiatives to expand self-serve analytics

With the COVID lockdowns, physical access to places and people was limited; organizations had to undertake data democratization initiatives in a world of hybrid work and distributed workforces. Across the globe, businesses were forced to put new digital safeguards in place. Role-based access control (RBAC), along with end-to-end encryption and multi-cloud to comply with data residency requirements, became critically important to ensure data integrity, availability, accuracy and confidentiality. (If you’re wondering how to comply with data residency and related requirements, take a look at our recent guide, which walks you through common definitions and compliance options.)

These data safeguards allowed organizations to continue business operations on a global scale without compromising data security or compliance — and more secure data access opened the door to self-service analytics, which freed up data teams to focus on more advanced projects, as opposed to basic reporting.

Consider how you can leverage data security initiatives to expand data democratization and self-serve analytics. That should enable your data team to do more without additional resources or headcount.

Re-evaluate your data strategy

While trying to provide business users reliable access to data and insights, ask yourself: What are our bottlenecks, and could they become enablers? If you think the answer is yes, you’re probably right.

Let’s take a quick look at two examples.

Resources

Executing any type of data project requires resources: budget, time, expertise, etc. Planning and brainstorming about how to secure those resources for a given data project is a bottleneck for many organizations — and that’s particularly true in a pandemic or unpredictable economy. 

However, leveraging prebuilt, scalable resources and automating wherever possible can turn a lack of resources into an enabler, as your team can now operate effectively with less budget and less bandwidth.

Outdated services

Recent advances in data technology mean you can often serve customers better with fewer resources and less risk. Ask yourself whether new tools would allow you to complete projects with less time, effort, resources and risk:

  • How could you expand and diversify the services you use?
  • Could you ingest customer data alongside your own data to provide them insights?
  • Could you unlock historical analysis within your data sources?
  • Is there a way to anonymize data as it enters a destination? 

These are just a few questions you could be asking yourself regularly. If your current platform or service isn’t able to help you innovate and better serve customers over time, consider addressing that in a way that helps you turn bottlenecks into enablers.

Consider automated ELT

In uncertain markets, businesses invest in data to clarify their business vision and identify their requirements to generate impact, improve customer retention rates and outperform the competition.

At Fivetran, our mission is to make data access as simple and reliable as electricity — and to allow your data team to do more with limited resources by eliminating your data engineering overhead. We offer over 200 fully managed, automated data connectors that you can set up in minutes. 

If you’re wondering whether you can save time or money by building the data pipelines yourself, we highly recommend “Build vs. Buy Data Integration,” which walks you through the basic calculations involved in comparing prebuilt and DIY data integration solutions. (Spoiler alert: Building data pipelines yourself almost always costs more.)

Check out our customer case studies for detailed examples of how we’ve helped data teams more efficiently serve stakeholders across departments — including in marketing, finance, sales and customer success analytics.

You can also sign up for our 14-day free trial to see how easy we make it to get your data from source to destination — with no coding required and a thoughtful ERD for every SaaS source.

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