If you’re like most companies, you’re collecting large volumes of data from a variety of data sources across different business units. What we typically see from the companies we work with is...
- Sales Data – a CRM that tracks all your customer sales data such as who bought what, when, how often, how much and at what price
- Marketing Data – data coming from your website that tracks everything from user behaviour, SEO, conversion funnels, various ad platforms with all your campaigns, all your email, social media, and a variety of others tools marketers use to understand the customer and the buyer’s journey
- Product Data – various tools tracking everything from projects, IT tickets, customer success, even external data
- Finance Data – an ERP that tracks your operating expenses such as accounting, procurement, project management, risk management, and compliance
- HR Data – various software tools that track all your employees’ acquisition, churn rate, salaries, onboarding and governance, capital expenses, etc.
To truly become data-driven, companies should ask themselves the following questions:
1. Do you have a well-defined data strategy that is written down?
A data strategy helps ensure your data is appropriately managed for critical business decisions and other applications. Using data to serve your business best starts with asking questions you want your data to answer (what product has the highest margin, what is our customer acquisition cost, who are my top performing salespeople?). Then establishing processes, practices, and policies to manage, use, and share data across your organization and external partners.
Your data strategy should include multiple data management initiatives such as:
- Data storage – where is my data being stored?
- Data integration – how do I access my data?
- Data migration – how do I get my data on the cloud?
- Data quality – how do I know if my data is reliable?
- Data governance – how do I manage who has access to my data?
- Data security – how do I protect my data?
- Data compliance – how do I ensure my data is compliant?
Part of your data strategy should also be determining roles and responsibilities, timelines for data projects, budgets, and tools, and bringing in strategic data partners with the specialized expertise to help you with your data challenges.
2. Do you have an efficient way to converge all your data into one platform?
Extracting data from multiple data sources requires an automation mindset. We’ve seen many customers attempt this manually and run into various challenges. It often takes weeks to run a single report, which is not a good ROE (return on the energy or effort). It requires much effort, bandwidth, and stress and is highly prone to human error.
Ideally, all your data sources would be integrated into one platform, and this process would be automated. This will enable you to extract live data automatically using software and code so that your data goes directly into your BI tool to update your dashboards and reports. This will give you quicker time to value, be less prone to human error, and you will have higher confidence in your data.
3. Do you have an easy and secure way to share data with proper data governance?
Traditional approaches to data sharing are inefficient and ineffective. Sharing vast amounts of data is impractical, if not impossible. It requires making a copy of the data and manually moving it somewhere (usually via email), which has a host of challenges such as it is cumbersome, time-consuming, have data security and governance risks; there are limitations to how much data you can share, and the data is always static, never live.
An ideal solution would be to share limitless amounts of live data easily, effortlessly, and instantly with proper security and governance protocols. Snowflake enables organizations to do just this.
Data sharing with Snowflake's Data Exchange breaks down these silos by providing access to live data between internal business units and external partners. Instead of a complex and cumbersome process, users can share and receive live read-only copies of data within minutes. This is done without having to move the data, so the data sharer is always in control, which greatly reduces the security and governance risks.
For further reading, check out: Data Sharing and the Future of Data Warehousing in the Cloud.
4. Do you trust your data?
If you've ever worked with data, you will know many things can go wrong. Wrangling data and putting it into some BI tool is time-consuming, and you don't know if it is even reliable. We call this the high confidence, bad data trap. In other words, you have bad data, and you’re making business decisions based on bad data, and you don't even know it.
If you suspect an error in your data, it's not always easy to trace where it occurred. You often have to start from scratch, redo all the work, and double and triple-check things. Again, automating this process using code will remove human error and give you data that is reliable and easy to use.
5. Where is all your data being stored?
If you're still using traditional on-prem storage but would like to migrate to the cloud, we recommend Snowflake. Snowflake offers many benefits, including everything in SQL, a standard programming language that most businesses will know. Data sharing, data security, and data governance are made easy. It uses a pay-as-you-go model to scale up or down as needed, saving you a lot of money. Compared to on-prem solutions, which require upfront costs and ongoing monitoring and maintenance, a cloud-based solution such as Snowflake requires zero upfront costs and no maintenance. That is all handled by Snowflake. It also has separate storage and computing, so processes that typically take hours now happen in seconds.
For further reading, check out our post: Why We Chose Snowflake.
6. Do you have the right tools, people, and processes to make sense of the data?
Businesses strive to become increasingly data-driven, but investments are typically directed at the visible part of the iceberg — data analysis and data science, where value is realized through business intelligence practices. This often comes at the detriment of the data engineering foundations of the organization, leading to a very robust analytics platform generating wrong insights from bad data with high confidence.
This is where we come in.
Working with Infostrux
We are your data partners, taking on the many data engineering challenges to deliver curated and refined data that your team can then use to generate significant, reliable value for your business at an accelerated pace. We do this by building and managing automated data pipelines so that your data is centralized, cleaned, and modeled in alignment with your specific business requirements.
From small to medium-sized businesses with fewer data sources to large enterprises facing big data challenges, our team of data engineers can deliver data you can trust.
We are Snowflake-certified partners who can help you get up and running in Snowflake Data Cloud.
If you're looking to become more data-driven or for a better solution to some of your data challenges, let us know, and we’d be happy to discuss them with you.