Data Lake tech for tomorrow's marketer
Marketers in today’s ever data driven world are trying to find insights into the customers they serve. What channels are my most successful for conversion? What is my customer lifetime value? What unknown operational, behavioral, or social data are predictive of my buyer’s behavior? These are the questions a data lake strategy coupled with a strong analytics partner or hired analyst can help you answer. Of course, every business is different but with a focused effort your organization can quickly be on track to answer big, strategic or important tactical questions that will empower growth. According to Gartner, data lake technology is a centralized repository that holds data which is unaltered, an exact copy from where it was derived, and data that has been transformed for analytics. This means that there’s no need to structure your data before storing it and you can simply use it the way it is. Then, you can apply various kinds of analytics to the data so you get useful information. The reason why data lakes are used are many but one important example is to use tools, algorithms, and advanced analytics to provide you with in-depth insights into large amounts of unstructured data. For example, one might analyze a data set with a strategic purpose or question in mind. An analyst can dive into the data using statistical model building tool sets such as R, SAS, SPSS, and others. They can use great analysis tools such as Tableau, Domo, Python, Qlik, and Power BI for data visualization.
A data lake is often preferable to work within some scenarios versus a data warehouse which often is structured and organized because you don’t have to build a data model and data governance program before you can derive insights from the data.
Hence, data lakes are solving a major issue faced by users and corporations; by allowing them to obtain relevant insights from a source of unstructured data multiple times, data lakes take away the risk of being left with just structured data that can only be used for a specific purpose.
The Value of a Data LakeThere are numerous ways that a data lake can be beneficial to users by leveraging more data, through an extensive range of sources and within a small span of time.With greater use of structured data, data lake users can see an employment of new strategies within the company, especially to improve relations with a target population of consumers.
This is because a data lake will combine its data with analytics taken from various types of data sources including but not limited to, behavioral data, unstructured data, and transactional non-descriptive data that is typically “dark data” because it has no correlative focus on customer outcomes.
For example, what if you found out through your data analysis that your best customers are those who log in to your website 4 times per month or greater? Might you think more deeply about the customer journey you are providing to your customers overall and which customers are visiting and logging in to your website? Using this method, companies can study various strategies and learn about which one would be most profitable.
A data lake can prove to be advantageous for research and development as well because it can take a huge burden of comparing and analyzing data, off the shoulders of the research team. Teams can effortlessly test their hypothesis and various aspects of it by measuring it up against other studies in the field.
Choosing Tech for Data Lake ProcessingThe kind of tech you incorporate into your business for the sole purpose of structuring and then re-structuring data. Here are some of the options you have.
HadoopThis tech is most widely known for its flexibility and the value it generates from being an open source technology. For instance, there are developer libraries with predeveloped programming and tools for various types of functions and integrations.
Hadoop also has a full stack solution that allows for the mobility of data in ways that are very appealing to other engineers. In particular, one value proposition is the ability to integrate a Hadoop data lake with other technologies.
More importantly, Hadoop is vital for data lakes that are on-premise because of its optimized systems which make deployments instantaneous virtually. If you prefer cloud-based technology, Hadoop can be deployed into it so that a hybrid is created. As a result, a large-scale data lake is produced
AWSOn the other hand, AWS is more comprehensive and quite secure data lake service that is cloud-based, so users will be building their repository in cloud storage. Users will benefit from this because they can analyze whatever data is present, this includes unstructured data from devices that have access to the Internet of Things as well.
These are officially known as Azure data lakes and they give users the advantage of unlimited storage space, whether they intend to keep structured or unstructured data. This data lake processing technology already comes equipped with processing features and tools, like Azure Data Lake Analytics, which can go through data sets to uncover new trends and findings.
These examples are the most common as their use has proliferated extensively in the last decade, and they make for a good place to start if you’re researching data lake technology. While the above-mentioned technologies can be described as effective and practical, there are still various other options that you can choose from.
What’s more important is whether you’re confident that you possess the in-house expertise and knowledge you require in making an informed decision as to which solution will meet your needs best. A little extra knowledge goes a long way- Cruz Street can help you make the right choice with the help of our analytics experts and professionals.
The team at Cruz Street is well equipped to help by providing a "CDO on Demand" or essentially a fractional executive service who's job is to audit data, technology, and people at your organization necessary to execute the strategy you want. Our team will help you both with a strategic road map and with data architecture, data acquisition, solution negotiation and more. Contact us today for an expert consultation!