Good Data Science starts with a deep understanding of how data should be manipulated and stored. Traditional data and big data need different approaches but the underlying discipline is the same. The way we store data differs greatly and we can advise on how to adapt your platforms for better insight generation.
Good Data Science starts with good data and this needs a deep understanding of how data should be manipulated and stored. Traditional data and big data need different approaches, but the underlying discipline is the same. The way we store data in legacy systems is not always appropriate for data science and we can advise on how to adopt your platforms for better insight generation.
Companies are very experienced in implementing data processing for business transactions.
In the majority of cases, this will involve a classical database solution. These systems have evolved to be very useful tools in processing transactions. Unfortunately, databases are not well tuned to perform analysis and visualization. Many companies add on technologies such as online analytical processing after the fact to address this issue.
Modern data science needs a data processing environment that can scale both the space available and the processing power provided. Scaling a database is possible but is a costly and time-consuming exercise.
A good data science processing environment will allow for many different types of data. From large data sets to small, structured data to unstructured. It should also accommodate both internal and external data; the environment must be able to do it all.
Very often the cloud is the best solutions for data science processing needs. Cloud based solutions take away all the worry around reliability, availability and managing backups from the data scientist. They are also designed to scale in size with extreme ease. The large cloud providers also offer mechanisms for analyzing and visualizing data.
Having set up your environment you will have to complete a few steps. Firstly, you should build the processes to gather data and store data. These processes streamline later work by preprocessing the data as it enters the data analysis environment. For example the processes can cleaned the data, change the data to use terminology that the business understands, and write it in a format that is highly efficient. It would also be a good idea to monitor and log these processes.
Business Intelligence (BI)
From simple reports to complete BI strategy that fully meets your business needs, we can help. Enjoy the flexibility that mobile and self-service BI brings to an organization without re-inventing the wheel.Read More
Market segmentation involves dividing customers into groups of people with similar characteristics or interests in order to make your marketing more effective.Read More
We have built many market models for our clients over the years allowing them to better understand the dynamics of the market and also to measure their performance. Market models explain what happened in the recent past and also allow us to forecast what is likely to happen.Read More
We can apply complex algorithms and Machine Learning and techniques of predictive analytics to a great variety of problems. Advanced analytics is a subset of data science that uses high-level techniques to predict future trends and behaviours.Read More
Text Matching and Analytics
Being able to match two data sources is vital to good analysis and we have a proven track record and methodology. We can also apply statistical and machine learning techniques to textual data to extract information and sentiment from the data.Read More
We take integrated security very seriously at JTA. We have the most stringent security practices and hold ourselves to a higher standard than most. JTA can build dashboards that intelligently adapt their content depending on who is viewing it to help users comply with corporate accountability legislation.Read More
Predictive maintenance is a benefit that we can bring to an organization by predicting failures and quality issues. This can avoid downtime and reduce maintenance costs.Read More
Using data prediction to identify when a certain customer is at high risk of churn allow clients to prevent attrition and keep existing clients. This helps immeasurably and keeps you with one in the hand rather than two in the bush.Read More
Internet of Things
The Internet of Things is the network of small devices that have an embedded processor to measure, control and connect to the internet. Many such devices benefit from sophisticated algorithms and data science techniques. We can develop solutions ready to roll out for deployment on the microcontroller.Read More
Companies which prefer to outsource data analytics instead of deploying a solution in-house can use JTA to form a virtual team to manage outsourced data analysis. Our team would typically access your data and your infrastructure and do the analysis remotely.Read More
Market Basket Analysis
Market Basket Analysis help companies understand how their customers make purchases. The objective is to help to configure sales promotions, loyalty programs and store layout.Read More