6 Steps Towards Better Data Management for Startups
Businesses nowadays accumulate tons of data, whether it is information collected through 3rd party tools like Google Analytics, or the data that is being stored within a site’s backend, like a MySQL database.
What many of these companies don’t realize is the importance of data. In today’s world, data is a valuable business asset and enterprises that haven’t reached this conclusion yet are in for a rude awakening.
Data is of particular importance for startup businesses that need all of the advantages that they can muster. Instead of relying on vague industry benchmarks for various KPIs, startup businesses need to realize the full potential of their data and use it as the source of their benchmarks.
Each business is unique and relying on outside sources to deliver the proper business goals for your company is often pretty ineffective. Here’s how startups can exploit their data to improve decision-making, operations and even targeted marketing campaigns.
Structure Your Data
The global data management market is expanding at an annual growth rate of over 14%. Data Management offers businesses flexibility, accessibility, and advanced analytics capabilities. That’s why structuring data should be one of the priorities for any company. By ‘structuring data’ we mean setting up a data management system that allows the capturing, storing and processing of said data.
Of course, it all depends on your business and the types of interactions that you have with customers, but you always need to aim for the highest level of transparency in data management.
A simple example would be an email complaint from a client. You can log its details into the database, but it’s going to be hard to analyze in the context of business goals. You could just take that email, assign it a value, for example, ‘negative’ for a complaint and log it, adding text as additional information.
Dissect Your Data
While there’s machine learning, natural language processing, and all sorts of other cool buzzwords within advanced data analytics, it’s still important to know your data. Even if you want to apply some of these cool techniques to your data in the future, you need to be able to understand the outcomes that you want to predict and what data is relevant to your business goals.
Here’s a basic example: store visits aren’t an important metric until paired with the dates these visits occurred. This information will allow you to predict store visits and adjust your operations accordingly with ease. But to know these dependencies you have sift through data, fiddle with it, see what metrics could be exploited and decide what’s junk.
Don’t Just Analyze It
Advanced analytical capabilities are no longer available exclusively to big enterprises. So startups shouldn’t be discouraged from exploring advanced analytical capabilities via machine learning and other AI techniques. For example, Amazon offers machine learning for smaller businesses at affordable prices.
These innovations should drive startups, as data is an untapped source of insights and growth. Just look at chatbots and how they can transform business operations using the data that you already feed them with. Imagine how that power can be applied to every facet of your operations.
Keep It Safe
We hope that you don’t store your data on a physical server in your back office. It’s 2017, after all. Unless you have some mind blowing IP that no-one should access. Even if you store your data in the cloud, there are still precautions to be taken, as even cloud services fail from time to time:
- Conduct data security training for your personnel
- Create an airtight bubble around your office by using secure network protocols, like Kerberos
- Don’t open emails that you’re not sure about
- Don’t post online, unless you want that information to be available to anyone, forever. Social engineering is the most effective hacking method.
Data is only valuable when people can access it. It doesn’t make sense to limit access to specific datasets or databases unless there is a security risk involved. Empower your employees to be able to access the data that you store so that they can drive their business initiatives in a more informed manner. Your marketers need numbers to throw around. Your engineers need use cases to drive product improvements. Your HR department needs success stories to attract top talent. And so on.
All of these people rely on enterprise data in one form or another. It’s time to democratize access to and unleash the creativity that comes with all of this knowledge.
Learn How to Use It
There are tons of things that business can do with their data. Don’t neglect the stories that it’s telling you. Don’t put personal opinion above data unless you have solid evidence to back up your point of view.
Know all of the facets of your business that can use big data, like marketing and sales, as these areas of business development rely heavily on understanding clients and their needs. Your treasure trove of big data is what they’ve been looking for.
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InData Labs helps tech startups and enterprises explore new ways of leveraging data, implement highly complex and innovative projects, and build breakthrough AI products, using machine learning, AI and Big Data technologies. Our core services include Big Data Consulting, Big Data Engineering, Data Science and AI Solutions Development.