Data analytics platforms enable businesses to collect, store, organize, analyze, and model raw data. Companies can leverage Data & Analytics such as machine learning (ML) and artificial intelligence (AI) to efficiently and accurately contend with vast data and deliver actionable insights. Many platforms are available on the market, and choosing between platforms can be challenging.
This guide provides tips for choosing a data analytics platform. Let’s dive in.
1. Identify Goals
The first crucial step in any business decision-making process is to identify goals clearly. Consult with key stakeholders and determine the problems that need to be solved or the new opportunities that are desired. It is likely that some points are already understood, hence the interest in learning how to choose a data analytics platform. However, it is necessary to put forth the time and effort to ensure each goal fulfills SMART standards, meaning each goal is specific, measurable, achievable, relevant, and time-bound. Articulating goals to this degree makes it easier to choose a data analytics platform that will
help achieve the goals.
2. Assess the Business
The next step in the process is to create a detailed picture of the state of the business. Clarify the financial budget, review the software and tools already in place, identify the capabilities of the IT team, identify the types of data the business uses, and how the data fits into operations as a whole. Here are some questions to answer during the assessment:
- What data sources are currently available?
- What data needs to be collected or integrated for future analytics initiatives?
- What are the projected needs for scaling data over time?
- What storage infrastructure is available or in place?
- What is the budget for implementing and maintaining a data analytics platform?
- How is data currently handled?
- Who handles the data currently?
- What IT and data science skills does the team have?
- What IT and data science skills are needed?
- What are the business’s data security, privacy, and regulatory requirements?
- What are the specific use cases or scenarios where the data will be applied?
- What is the preferred deployment model: cloud-based, on-premises, or hybrid, and why?
3. Consider the Users
Another crucial consideration in the decision-making process is the user. After all, the data analytics platform should cater to the user's needs. Who in the team will use the platform, and what for? Consider their capabilities and perspectives. Are they experienced data scientists and engineers who can operate complex models, or are they non-technical employees? It is also essential to consider how the users feel about the existing infrastructure and learn what they identify as needs for the new program. Regardless of where the current operators stand, ensure the program is user-friendly and equipped with data visualization tools so insights can be compellingly presented to all stakeholders.
4. Research Solutions
Once the internal needs and capabilities are identified, it is time to review available platforms. To gain a deeper understanding of the available platforms, investigate the following topics for each platform:
- Implementation speed
- User interface
- Data modeling and visualization capabilities
- Storage infrastructure
- Data backup and disaster recovery capabilities
- UX capabilities
- Security standards
- Ability to support regulatory requirements
- User support capabilities
- Industry-specific templates
- Customizability
- Availability of third-party extensions
- Scalability
- Pricing structure
As part of the research, it can be helpful to review existing use cases to gain real-life references for each analytics platform. Look for industry-specific examples to understand how the platform supports the distinct needs of similar businesses.
5. Think of the Future
While many priorities may be focused on the short term, thinking long-term is just as important. Choose a platform with scalability and agility in mind. To prepare for future success and drive growth, the platform needs to be able to process large data sets and new data sources. The platform must also be easy to update. It can be costly to change analytics platforms in the future, so it is best to choose a platform that is designed with the future in mind.
6. Get Expert Advice
Through expert Data & Analytics solutions, Encora helps companies unleash the potential of data. Encora’s data analytics allows companies to analyze historical data and make accurate, data-driven decisions for improved efficiency and effectiveness.
Fast-growing tech companies partner with Encora to outsource product development and drive growth. We are deeply expert in the various disciplines, tools, and technologies that power the emerging economy, and this is one of the primary reasons that clients choose Encora over the many strategic alternatives that they have.
To choose the best data analytics platform for your enterprise, contact Encora.
