(IoT), Enterprise search and Application programming interface (API)
Fast data is one of the most important things in big data. However, data movement and data sharing are equally important. This is because huge volumes of data are created in the past 12 months alone and million new devices connected to the internet. Likewise, many tools and applications are created on a daily basis to fill the on-demands of both the internet and technology usage.
New data is stored and managed. It is also sought for business purposes. However, the biggest challenge is not about storing and searching the data. It is about learning, analysing and distributing the data in real time. It is learning deeply what you can program. All this points to the facts that the Internet of thing challenges are real, and we need to be prepared how to cope with them. Furthermore, the availability of strong bandwidth networks for internet purposes is not available in all regions, hence being also another challenge in big data applications.
These are eight pillars that are essential for data-driven agile company;
- Data ingest
- Data store
- Data distribution
- Data security
- Data search
- Data Analysing
- API traffic
- Data visualizing
- Why data ingesting?
No matter which format or database you need to store. One has to ingest structured, semi-structured and unstructured data without any limitation about the connectors, API or frameworks that understand the scheme based and schema-less data. Data storing and distributing are equally important because you need to store valuable data. If it does not fit a single computer, you need to spread to multiple computers or discs. Hadoop is the technology that can handle the volume of data without any problem.
Enterprise search engines
Seeking information is an important part of big data because users from desktop or handheld devices need to find information online and on a dashboard by using query-based search or voice. No matter how much we seek relevant information everybody knows the searching information is essential for every company, small or large. Search technologies are becoming more and cleverer these days because searching text (full-text search) alone is no longer the case. People want to search information without even typing a word but talk on the microphone for voice search. Voice search is very popular in online search engines. It is because information is simply too much even for incoming email one cannot handle and remember every sender’s name, email address and the topic title. People are hungry to save time on reading a lot of information and act accordingly. They are rather searching relevant information by reducing the amount of time they spend on getting information.
There are several data engines out there including Apache Solr and Elastic search. However in reality HP IDOL is still the leader of enterprise search technology for finding meaningful information that users need. HP IDOL has a unique capability in meaning-based contextual search and it has an unmatched algorithm for keyword and content search. It has an intelligent algorithm and is “Language agnostic”.
HP IDOL’s 400 connectors enable the engine to ingest different data types without any limitation for which formats. This search engine can search information whether in a piece of text, hours of video or audio files. On the other hand, ingesting data from different repositories is necessary. That is why people use Hadoop ecosystem connectors for retrieving data from various data sources while maintain storing, distributing and managing the data across different computers. Scheme fewer data technologies are out there to achieve this. However, businesses that understand their data are becoming data driven agile companies. Searching relevant information from the data lake and getting a meaning -full answer is important.
Since every single bit of data are so essential to business and decision making, analyzing it is equally significant and showing the insight. Using software like Tibco Spotfire shows the needed patterns that you want to see. Relevant information is rather reading content or viewing pictures hours or even days to see the information that is pertinent to make a decision. As the data grows, learning about human eyes is getting dryer and reading irrelevant information is not great for many readers. One has to think of visualization software like Tibco to see the data in a big picture. “Let me say image more”! a visualization tool enables the people to see the relevant information differently.