big data, Big 5 Predictions For Big Data

Big data has piqued universal interest, whether a company’s focus is on artificial intelligence (AI) or fashion design. Information is the most priceless commodity out there, but organizing and maintaining it poses challenges. This is even more notable in businesses that have not pursued digital transformation yet. These are the ways to overcome the most present obstacles in big data integration so everyone can get the most out of its impact. 

Common Hurdles in Big Data 

Every corporation, regardless of sector, has numerous entry points for data. Employee applications, customer service calls, social media, inventory numbers, partner feedback and client management only scratch the surface. These silos represent what big data has to offer, but they are disparate and can’t generate insights when separate.  

Every item in the tech stack could store information in varying formats as well, complicating matters further by making data incompatible with each other. Therefore, merging them into singular locations could prove labor- and time-intensive. It would require translating everything into streamlined formats, occupying employees for months on end.  

The data never stops incoming. Its ever-increasing nature will only make the extraction, transformation and loading tasks progressively more daunting. The more an enterprise puts off big data integration, the more it sacrifices integrity. Information accuracy and timeliness get lost as time passes. 

Finally, many teams lack adequate support for constant monitoring, observation and cleaning. Data requires a lot of attention and hands-on surveillance to keep it high quality.  

Actions to Take 

What can workplaces do to address these prevalent concerns? 

Establish Strong Data Governance 

Companies must choose the data architecture they want. Data warehouses, lakes and lakehouses are the primary options for unifying platforms. Each is optimized for storing unstructured or structured information, depending on the team’s processing capabilities.  

Connecting assets to cloud infrastructure is also ideal for enhanced collaboration and visibility. Many of these systems automate categorizing or scanning for duplicates. These actions are foundational for strong data governance, promising incoming information and processing activities are consistent and secure. 

Undergo Data Normalization 

Many organizations need to make information consistent, normalizing the state before importing it into housing. Middleware is an ideal problem-solver because it assists with bridging the gap between legacy systems and aspirational big data solutions. 

Use Advanced Analytics Tools 

Analytics tools, especially embedded with AI and machine learning algorithms, are powerful for parsing large amounts of information at once. It makes big data feel accessible. These tools also make it more manageable to integrate a big data strategy because it can discover gaps, outliers and anomalies in a seemingly endless sea of information that would be impossible for humans to sift through completely. 

Successful integration could lead to boosted revenue or insightful discoveries previously hidden before the company collated the data. Visibility can have impactful advantages, especially when used for projects like reducing factors contributing to homelessness or informing aid teams responding to crises. 

Strategic Integration Tips 

Companies want to ensure they have pooled information from as many datasets as possible. Experts should think outside the box to verify they have everything. Here are a few examples of resources containing business-critical data that companies can meld with big-data organization solutions: 

  • Enterprise resource management 
  • Customer relationship management 
  • Support system data 
  • Website application data 

Not all these locations have equal cybersecurity, so IT experts and analysts should ensure all information is safe before moving it into new architecture. This could prevent data poisoning, breaches and vulnerabilities in the future. Teams must implement defensive practices immediately, such as least-privilege rules, encryption and data minimization. 

Ultimately, all integration objectives should revolve around a company’s values and goals. This could be for scaling, knowledge-sharing or expanding into new verticals. Data could become unwieldy without organizational guiding principles. Experts may have too much unnecessary information clouding results because they assume they need everything when they do not.  

Big Data Boons 

Big data feels too good to be true. It promises never-before-seen revelations, allowing experts to operate in the most productive and efficient ways their companies have witnessed. However, the complex integration process and its consistently present hurdles make these advantages seem challenging to achieve.  

Everyone has the opportunity to use big data to their advantage. Countless tools and tips are available for all skill levels to make it a regular fixture of innovative problem-solving and creative ideation.