For companies looking to leverage big data analytics, the first step is getting connected. But as device selection, method of connection, and infrastructure begin to come into focus, it becomes clear that big data analytics tools are required to parse, manage, and shape the data into actionable insights.
It also means that decision-makers must choose the tools best suited for their use case. That could mean choosing industry-specific software. Or, for sensitive, health-related, or financial processes, it may mean a commitment to big data security analytics tools. The question all companies face is: what type of data do we need to analyze, and what value are we trying to achieve?
Considerations for Selecting Big Data Analytics Tools
Big data analytics tools leverage the massive volume of data produced by a company’s processes. Mining this business activity data can achieve greater competitiveness, more optimized processes, lower costs, and even new value-added services or products.
Selecting the right analytics tools to fit your business strategy is essential. Here are a few key considerations:
· Interoperability
Most companies will likely need to continue to use existing software. In these cases, any data analytics tools must be interoperable across other platforms. They should at the least fit well into MRP or ERP systems as well as any financial software. The most straightforward and flexible software platforms allow connectivity and interoperability through API connection.
· Skillsets
While many companies have high-tech skillsets in-house, small and medium-sized businesses (SMBs), startups, and new enterprises may not. Users may be ordinary employees. If tech skillsets are exceptionally low or extremely high, the selection of analytics tools should be influenced accordingly.
· Scalability
Many SMBs are eager to utilize big data analytics tools because the value created by such software puts them on par with larger companies and levels the playing field. But the system must be modular, cloud-based, and able to scale for such companies. Larger enterprises with single-digit steady growth will have quite different scalability needs for analytics tools than a small company whose business volume doubles, triples, or more each year.
Choosing the Software
There are many big data analytics software companies on the market. And each targets a specific type of analysis and customer. Here are a few of the best-known data analytics companies.
1. Tableau
Tableau is highly centered on visualization. Using multiple data inputs, users can arrange different combinations of crucial data without having to be data scientists. These insights are then easily viewed through dashboards.
2. Microsoft
It’s not surprising that one of the largest software companies would have a big data analytics tool. Microsoft’s popular Azure Cloud hosts the Power BI platform with many artificial intelligence (AI) and machine learning (ML) functions. Because of Microsoft’s reach, Power BI is interoperable with any Microsoft software.
3. R-Programming
For companies with a higher degree of technical skillsets or in-house data scientists, R-Programming allows for customizing statistical engines. This focus on statistical analysis can be used for plots, charts, and graphics that reveal insights into a company’s data.
4. Apache Hadoop
For open-source fans and cost-conscious companies, Hadoop can be run on a distributed server network and accept data from commodity hardware. It uses several platforms in a software ecosystem that takes advantage of the distributed data while still allowing robust analytics.
5. SAS
Like Microsoft, SAS has been around for a long time and has specialized in data analysis longer than most. It is often used in heavy-hitting data science but is still valuable to less-qualified staff. SAS can produce complex models, data preparation, and advanced trend analysis. It can be tied to factory automation systems and has a reliable predictive capability.
6. RapidMiner
Another open-source entry that may make sense for cost-conscious SMBs and startups is RapidMiner. Its power lies in an intuitive graphical user interface that helps users create an analysis process for their business. For open-source software, RapidMiner is reliable for built-in security, and it can manage large datasets.
7. Zoho Analytics
Zoho is another long-time player with a powerful reputation in predictive analytics. Their platform is accessible to SMBs due to its low cost. Many SMBs take advantage of Google for email, documents, spreadsheets, and meetings. Zoho leverages this tendency to its advantage by being fully integrative with Google.
Help in Deciding on Big Data Analytics
These are a few of the dozens of software platforms available to companies of all sizes. And entrepreneurs and startup businesses should not be timid about finding the right data analytics platform that fits their size and budget.
But suppose you are still unsure how to take advantage of big data analytics best or how it fits into your business. In that case, the Henry Bernick Entrepreneurship Centre (HBEC) at Georgian College can help. With assistance for new business owners in innovation, entrepreneurship, R&D, and business mentoring, HBEC has academic and business expertise that can help guide you as part of your entrepreneurial journey.
Our programs are committed to including cutting-edge technology and big data business analytics as part of our overall training and mentoring of the leaders of today and the future. To find out how our programs can assist your path to success, contact us today.
