Most people’s understanding of data science technology ends where computers begin. But while it’s sometimes difficult to understand data science, it’s still necessary to keep up on it.
Understanding predictions and trends will allow you to plan better for the future. You don’t have to understand the technology to get what it does, either, so there’s nothing stopping you from being in the loop of advances in data science.
So, what can we expect from 2019?
Data Science, AI, and What Comes Next
The general trend in data science seems to be a unification of knowledge. That is, things are getting more connected and easier to access. Advances in technology are sure to bring more access to information that is easy to digest and use to improve business.
1. Graphs and Time Series Will Be More Available
You can expect to have a better ability to engage with the complex data from time series and graphs. Time series, in particular, are often dense and difficult to digest.
Technology that allows us to store and interpret large volumes of data are emerging. These tools will help companies with big picture ideas and options by compressing extensive information into more succinct graphics and analysis.
2. Companies Will Pair Their Data
Businesses are predicted to start sharing their data through platforms designed to combine information. Access to common data will promote uniformity in the market and allow companies to grow more communally.
Before everyone starts holding hands, though, it’s more likely that companies will use data sharing technology to synchronize data amongst their own departments. If data can be pooled across a company’s organizational lines, it can be used to make general insights that could greatly benefit the organization.
3. Artificial Intelligence and Machine Learning
If you weren’t sure, AI and machine learning are two different concepts. They kind of appear the same at first glance.
AI is the reality of machines making intelligent decisions and acting pseudo-independently. Machine learning is more the end of technology that absorbs and processes information. Processing information is essential to data science technology.
It appears that machine learning, much like companies themselves, is moving towards collaboration. Where companies are seeking to share and capitalize on their data together, machines will begin pulling data from different sources.
These data pipelines will be extremely well informed and allow multiple companies to tap into a wealth of extremely relevant and well-rounded information.
4. Deep Learning Will Have More Impact
Deep learning is an element of artificial intelligence that learns information through algorithms that are representative of the structure of the human brain. The brain uses neural networks, and deep learning uses artificial ones.
Older algorithms had a larger learning curve than artificial neural networks, as well as having lower memory capacity. Deep learning is slated to have a larger impact on data science.
The new areas it will touch are largely related to search engine optimization and securities. There will also be a focus on time series analysis and understanding.
5. Storage Systems Will Blend New and Old
There’s a rift between the current data input and historical data. The software that analyzes data in real time is typically separate from software that looks at past data.
Companies currently use a number of https://www.logianalytics.com/resources/bi-encyclopedia/data-source-types/. These consist of streaming systems, data warehouses, and other pools of historical data. The existence of so many inputs is costly and difficult to synthesize.
Not to mention, the time spent incorporating new and old data could be better spent on something else. This is why an increased focus has been put on systems that blend the old and new into one source.
Technology is lacking in this department, but the need for technology has become apparent and it’s likely that advances are coming soon.
Data Scientists Will Be in High Demand
With the rising need for advanced data technology, professionals in the field will be in higher demand. The skillset needed to improve the already complicated field is highly sought after in nearly every industry.
The need isn’t limited to one area, either. Data science commonly branches into the fields of statistics and predictive analysis. That focus will shift toward data mining, technological understanding, and business prowess.
Data science is evolving out of a strictly predictive and analytical mode and moving toward a focus on web technology and the synthesis of current technologies. Stats and analytics are still extremely important, but it’s good to keep in mind that the field is branching out into different focuses.
This means more jobs, higher demand, and more job security. Companies will always need individuals who can predict the best next move, understand the past of an industry, and have an insight into what the industry holds in the future.
Staying ahead of the competition is key. That being said, business is certainly not the only aspect of data science that promises career opportunities.
A Few Career Possibilities
Most data science paths will involve analyzing data and making predictions. That skillset melts into nearly every professional industry. Biological and social systems, for example, offer an interesting avenue to get involved in the industry.
For a career in a biological or social field, you’ll need a science background as well as an understanding of computer technology and statistics. The field is expected to grow in the upcoming years and boasts an average salary of 100,000 dollars per year.
Another possibility comes in the form of data security. Computer networks are extremely valuable and therefore they are targeted by cyber-criminals. You could choose to work to improve security measures and solve problems related to cyber-security and data protection.
Interested in a Career?
If you’re interested in a career in data science, there’s no better time than now to get started. The industry is expected to grow in the near future and the value of data scientists is already high.
For more information on data science and the career possibilities it offers, visit our site and get started.