Written by Bobbi Sanchez
Do you waste time every week searching for data? The Data Warehousing Institute estimates that U.S. businesses lose a cumulative 600 billion dollars a year due to problems with data quality.
Organizations that find solutions to data challenges gain significant advantages over competitors. With that in mind, forward-looking organizations are interested in big data trends for the future. Big data 2019 trends include an increased move to cloud computing, more use of streaming analytics and increased data governance.
Without good data management, organizations miss out on the insights that could help them to make better business decisions and increase profits.
Data management involves acquiring, validating, storing, protecting, and using data in an accessible, reliable, and meaningful way. It takes time and effort and becomes increasingly difficult as volumes and velocity of incoming data increase.
Well-managed data is readily available, better organized and easier to work with. It reveals trends, patterns, and associations that enable better decision-making. Here are some of the big data 2019 trends that are helping organizations turn huge data collections into actionable insights.
As big data becomes a “must-have,” more companies are looking into cloud computing to make management and analysis faster and more efficient. Cloud computing enables them to establish big data infrastructure in a scalable, fast way and cut costs because they don’t have to maintain big data centers in-house.
Cloud database providers are using machine learning to make service offerings autonomous. They are offering big data infrastructure with end-to-end automation.
Cloud systems are being cost-optimized even further and we’ll see more organizations turning to cold data storage solutions. They will be able to park older, unused data in cold storage and save as much as 50% on storage costs.
Streaming data comes from a web of connected devices and reaches the IT systems of an organization in real-time. To manage this, companies need streaming analytics. The quicker an organization can act on data, the better off it is and that is the driving force behind streaming, or real-time, analytics.
Cloud-based platforms are able to capture real-time data across devices and networks and process the information in real-time to enable them to accomplish mission-critical tasks quickly and effectively. Aside from real-time business intelligence reporting, there are many more use cases for streaming analytics, from cybersecurity to predictive maintenance.
Data governance is building steam as companies increasingly realize that handling data carelessly poses a risk. Data breaches are bringing the issue to a head and most companies realize that the Wild West days of big data are coming to an end.
The European Union enacted the General Data Protection Regulation (GDPR) last year and while there is no similar law in the U.S. yet, poor data governance is becoming increasingly unacceptable.
Many companies face the need to manage unstructured data. A marketing company, for instance, may have unstructured data in the form of images, survey responses, transcripts, audio and video files.
Management isn’t possible through conventional data models and more spending is going into descriptive, predictive and content analytics. To take advantage of big data in marketing, the right systems and tools must be in place. It is also critical to have employees with the right skills.
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Trends in big data analytics include augmented analytics, where systems using AI and machine learning make accurate predictions and provide insights without human participation.
This means that insights based on big data will become increasingly available. The worldwide augmented analytics market is expected to grow to 18.4 billion by 2023.
Big data is changing the business world and has already significantly impacted sales and marketing. Most organizations use some form of analytics to predict market trends and measure engagement. Data analytics has become essential for personalized marketing and accurate audience targeting.
It’s the key to understanding buyer intent. To remain competitive in business today, companies have to adapt their strategies around using big data and analytics, applying it according to the requirements of the company.
Optimized data warehouses
Optimizing data warehouses is expensive and complex but crucial to efficient decision-making in an organization. Trends in big data analytics include the use of various different approaches to improve scalability and minimize costs.
Organizations are expanding deep learning beyond natural language processing (NLP) and computer vision. They are finding new and creative ways to implement deep learning. Large financial institutions have already discovered that neural network algorithms are able to spot fraud better than “traditional” machine learning approaches.
When it comes to the future of big data, most organizations realize that traditional data warehouses won’t cut it. They are looking at flexible data platforms that allow them to integrate and automate all data sources and types at scale. Progress is being made on many fronts and while big data presents various technical, legal and ethical hurdles, the potential benefits are too great to ignore.
Bobbi Sanchez is a tech expert whose main focus is on developing education systems through technology integration. He is of idea that quality education should be available to every student across the world to help them have a better future. In his free time, he plays guitar, plays with his lovely pups and writes blogs.